Retrieving data from a dispersed storage network in accordance with a retrieval threshold

ABSTRACT

A method begins with a processing module determining a retrieval threshold for retrieving a set of encoded data slices from a dispersed storage network (DSN). The set of encoded data slices represents data encoded using a dispersed storage error encoding function having a number of encoded data slices in the set of encoded data slices equal to or greater than a decode threshold and the retrieval threshold is equal to or greater than the decode threshold. The method continues with the processing module issuing data retrieval requests to the DSN for the set of encoded data slices and receiving encoded data slices of the set of encoded data slices to produce received encoded data slices. The method continues with the processing module decoding the received encoded data slices to recapture the data when a number of received encoded data slices compares favorably to the retrieval threshold.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. §120, as a continuation, to the following U.S. Utility patentapplication, which is hereby incorporated herein by reference in itsentirety and made part of the present U.S. Utility patent applicationfor all purposes:

-   -   1. U.S. Utility application Ser. No. 13/097,357 entitled        “RETRIEVING DATA FROM A DISPERSED STORAGE NETWORK IN ACCORDANCE        WITH A RETRIEVAL THRESHOLD,” (Attorney Docket No. CS00502),        filed Apr. 29, 2011, now U.S. Pat. No. 8,448,044, which claims        priority pursuant to 35 U.S.C. §119(e) to the following U.S.        Provisional Patent Application:        -   a. U.S. Provisional Application Ser. No. 61/346,173,            entitled “DISPERSED STORAGE NETWORK MEMORY DEVICE            UTILIZATION,” (Attorney Docket No. CS00336), filed May 19,            2010.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computing systems and moreparticularly to data storage solutions within such computing systems.

2. Description of Related Art

Computers are known to communicate, process, and store data. Suchcomputers range from wireless smart phones to data centers that supportmillions of web searches, stock trades, or on-line purchases every day.In general, a computing system generates data and/or manipulates datafrom one form into another. For instance, an image sensor of thecomputing system generates raw picture data and, using an imagecompression program (e.g., JPEG, MPEG, etc.), the computing systemmanipulates the raw picture data into a standardized compressed image.

With continued advances in processing speed and communication speed,computers are capable of processing real time multimedia data forapplications ranging from simple voice communications to streaming highdefinition video. As such, general-purpose information appliances arereplacing purpose-built communications devices (e.g., a telephone). Forexample, smart phones can support telephony communications but they arealso capable of text messaging and accessing the internet to performfunctions including email, web browsing, remote applications access, andmedia communications (e.g., telephony voice, image transfer, musicfiles, video files, real time video streaming. etc.).

Each type of computer is constructed and operates in accordance with oneor more communication, processing, and storage standards. As a result ofstandardization and with advances in technology, more and moreinformation content is being converted into digital formats. Forexample, more digital cameras are now being sold than film cameras, thusproducing more digital pictures. As another example, web-basedprogramming is becoming an alternative to over the air televisionbroadcasts and/or cable broadcasts. As further examples, papers, books,video entertainment, home video, etc. are now being stored digitally,which increases the demand on the storage function of computers.

A typical computer storage system includes one or more memory devicesaligned with the needs of the various operational aspects of thecomputer's processing and communication functions. Generally, theimmediacy of access dictates what type of memory device is used. Forexample, random access memory (RAM) memory can be accessed in any randomorder with a constant response time, thus it is typically used for cachememory and main memory. By contrast, memory device technologies thatrequire physical movement such as magnetic disks, tapes, and opticaldiscs, have a variable response time as the physical movement can takelonger than the data transfer, thus they are typically used forsecondary memory (e.g., hard drive, backup memory, etc.).

A computer's storage system will be compliant with one or more computerstorage standards that include, but are not limited to, network filesystem (NFS), flash file system (FFS), disk file system (DFS), smallcomputer system interface (SCSI), internet small computer systeminterface (iSCSI), file transfer protocol (FTP), and web-baseddistributed authoring and versioning (WebDAV). These standards specifythe data storage format (e.g., files, data objects, data blocks,directories, etc.) and interfacing between the computer's processingfunction and its storage system, which is a primary function of thecomputer's memory controller.

Despite the standardization of the computer and its storage system,memory devices fail; especially commercial grade memory devices thatutilize technologies incorporating physical movement (e.g., a discdrive). For example, it is fairly common for a disc drive to routinelysuffer from bit level corruption and to completely fail after threeyears of use. One solution is to a higher-grade disc drive, which addssignificant cost to a computer.

Another solution is to utilize multiple levels of redundant disc drivesto replicate the data into two or more copies. One such redundant driveapproach is called redundant array of independent discs (RAID). In aRAID device, a RAID controller adds parity data to the original databefore storing it across the array. The parity data is calculated fromthe original data such that the failure of a disc will not result in theloss of the original data. For example, RAID 5 uses three discs toprotect data from the failure of a single disc. The parity data, andassociated redundancy overhead data, reduces the storage capacity ofthree independent discs by one third (e.g., n−1=capacity). RAID 6 canrecover from a loss of two discs and requires a minimum of four discswith a storage capacity of n−2.

While RAID addresses the memory device failure issue, it is not withoutits own failures issues that affect its effectiveness, efficiency andsecurity. For instance, as more discs are added to the array, theprobability of a disc failure increases, which increases the demand formaintenance. For example, when a disc fails, it needs to be manuallyreplaced before another disc fails and the data stored in the RAIDdevice is lost. To reduce the risk of data loss, data on a RAID deviceis typically copied on to one or more other RAID devices. While thisaddresses the loss of data issue, it raises a security issue sincemultiple copies of data are available, which increases the chances ofunauthorized access. Further, as the amount of data being stored grows,the overhead of RAID devices becomes a non-trivial efficiency issue.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a computingsystem in accordance with the invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the invention;

FIG. 3 is a schematic block diagram of an embodiment of a distributedstorage processing unit in accordance with the invention;

FIG. 4 is a schematic block diagram of an embodiment of a grid module inaccordance with the invention;

FIG. 5 is a diagram of an example embodiment of error coded data slicecreation in accordance with the invention;

FIG. 6 is a flowchart illustrating an example of managing a memorydevice in accordance with invention;

FIG. 7 A is a flowchart illustrating an example of authorizing an accessrequest in accordance with the invention;

FIG. 7 B is a diagram illustrating an example of an authorization tablein accordance with the invention;

FIG. 8 A is a diagram illustrating an example of a memory utilizationmap sequence in accordance with invention;

FIG. 8 B is a flowchart illustrating an example of balancing memoryutilization in accordance with the invention;

FIG. 9 A is a flowchart illustrating an example of managing memory usagein accordance with the invention;

FIG. 9 B is a flowchart illustrating another example of managing memoryusage in accordance with the invention;

FIG. 9 C is a flowchart illustrating another example of managing memoryusage in accordance with invention;

FIG. 10 A is a diagram illustrating an example of a user role table inaccordance with invention;

FIG. 10 B is a diagram illustrating an example of a role permissionstable in accordance with the invention;

FIG. 10 C is a flowchart illustrating another example of authorizing anaccess request in accordance with the invention;

FIG. 11 is a flowchart illustrating an example of retrieving data inaccordance with invention;

FIG. 12 is a flowchart illustrating an example of synchronizing arevision of stored data in accordance with the invention;

FIG. 13 A is a diagram illustrating another example of a memoryutilization map in accordance with invention;

FIG. 13 B is a flowchart illustrating another example of balancingmemory utilization in accordance with the invention;

FIG. 14 A is a flowchart illustrating an example of identifying a failedmemory device in accordance with invention;

FIG. 14 B is a flowchart illustrating an example of processing a memoryaccess request in accordance with invention;

FIG. 15 is another schematic block diagram of an embodiment of acomputing system in accordance with the invention;

FIG. 16 is a flowchart illustrating an example of storing data inaccordance with the invention;

FIG. 17 is another schematic block diagram of an embodiment of acomputing system in accordance with the invention;

FIG. 18 is a flowchart illustrating another example of retrieving datain accordance with the invention; and

FIG. 19 is a flowchart illustrating an example of generating a passkeyin accordance with invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of a computing system 10 thatincludes one or more of a first type of user devices 12, one or more ofa second type of user devices 14, at least one distributed storage (DS)processing unit 16, at least one DS managing unit 18, at least onestorage integrity processing unit 20, and a distributed storage network(DSN) memory 22 coupled via a network 24. The network 24 may include oneor more wireless and/or wire lined communication systems; one or moreprivate intranet systems and/or public internet systems; and/or one ormore local area networks (LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of distributed storage (DS) units36 for storing data of the system. Each of the DS units 36 includes aprocessing module and memory and may be located at a geographicallydifferent site than the other DS units (e.g., one in Chicago, one inMilwaukee, etc.). The processing module may be a single processingdevice or a plurality of processing devices. Such a processing devicemay be a microprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module may have an associatedmemory and/or memory element, which may be a single memory device, aplurality of memory devices, and/or embedded circuitry of the processingmodule. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module includes morethan one processing device, the processing devices may be centrallylocated (e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that when the processing module implements one or more ofits functions via a state machine, analog circuitry, digital circuitry,and/or logic circuitry, the memory and/or memory element storing thecorresponding operational instructions may be embedded within, orexternal to, the circuitry comprising the state machine, analogcircuitry, digital circuitry, and/or logic circuitry. Still further notethat, the memory element stores, and the processing module executes,hard coded and/or operational instructions corresponding to at leastsome of the steps and/or functions illustrated in FIGS. 1-19.

Each of the user devices 12-14, the DS processing unit 16, the DSmanaging unit 18, and the storage integrity processing unit 20 may be aportable computing device (e.g., a social networking device, a gamingdevice, a cell phone, a smart phone, a personal digital assistant, adigital music player, a digital video player, a laptop computer, ahandheld computer, a video game controller, and/or any other portabledevice that includes a computing core) and/or a fixed computing device(e.g., a personal computer, a computer server, a cable set-top box, asatellite receiver, a television set, a printer, a fax machine, homeentertainment equipment, a video game console, and/or any type of homeor office computing equipment). Such a portable or fixed computingdevice includes a computing core 26 and one or more interfaces 30, 32,and/or 33. An embodiment of the computing core 26 will be described withreference to FIG. 2.

With respect to the interfaces, each of the interfaces 30, 32, and 33includes software and/or hardware to support one or more communicationlinks via the network 24 and/or directly. For example, interfaces 30support a communication link (wired, wireless, direct, via a LAN, viathe network 24, etc.) between the first type of user device 14 and theDS processing unit 16. As another example, DSN interface 32 supports aplurality of communication links via the network 24 between the DSNmemory 22 and the DS processing unit 16, the first type of user device12, and/or the storage integrity processing unit 20. As yet anotherexample, interface 33 supports a communication link between the DSmanaging unit 18 and any one of the other devices and/or units 12, 14,16, 20, and/or 22 via the network 24.

In general and with respect to data storage, the system 10 supportsthree primary functions: distributed network data storage management,distributed data storage and retrieval, and data storage integrityverification. In accordance with these three primary functions, data canbe distributedly stored in a plurality of physically different locationsand subsequently retrieved in a reliable and secure manner regardless offailures of individual storage devices, failures of network equipment,the duration of storage, the amount of data being stored, attempts athacking the data, etc.

The DS managing unit 18 performs distributed network data storagemanagement functions, which include establishing distributed datastorage parameters, performing network operations, performing networkadministration, and/or performing network maintenance. The DS managingunit 18 establishes the distributed data storage parameters (e.g.,allocation of virtual DSN memory space, distributed storage parameters,security parameters, billing information, user profile information,etc.) for one or more of the user devices 12-14 (e.g., established forindividual devices, established for a user group of devices, establishedfor public access by the user devices, etc.). For example, the DSmanaging unit 18 coordinates the creation of a vault (e.g., a virtualmemory block) within the DSN memory 22 for a user device (for a group ofdevices, or for public access). The DS managing unit 18 also determinesthe distributed data storage parameters for the vault. In particular,the DS managing unit 18 determines a number of slices (e.g., the numberthat a data segment of a data file and/or data block is partitioned intofor distributed storage) and a read threshold value (e.g., the minimumnumber of slices required to reconstruct the data segment).

As another example, the DS managing module 18 creates and stores,locally or within the DSN memory 22, user profile information. The userprofile information includes one or more of authentication information,permissions, and/or the security parameters. The security parameters mayinclude one or more of encryption/decryption scheme, one or moreencryption keys, key generation scheme, and data encoding/decodingscheme.

As yet another example, the DS managing unit 18 creates billinginformation for a particular user, user group, vault access, publicvault access, etc. For instance, the DS managing unit 18 tracks thenumber of times user accesses a private vault and/or public vaults,which can be used to generate a per-access bill. In another instance,the DS managing unit 18 tracks the amount of data stored and/orretrieved by a user device and/or a user group, which can be used togenerate a per-data-amount bill.

The DS managing unit 18 also performs network operations, networkadministration, and/or network maintenance. As at least part ofperforming the network operations and/or administration, the DS managingunit 18 monitors performance of the devices and/or units of the system10 for potential failures, determines the devices and/or unit'sactivation status, determines the devices' and/or units' loading, andany other system level operation that affects the performance level ofthe system 10. For example, the DS managing unit 18 receives andaggregates network management alarms, alerts, errors, statusinformation, performance information, and messages from the devices12-14 and/or the units 16, 20, 22. For example, the DS managing unit 18receives a simple network management protocol (SNMP) message regardingthe status of the DS processing unit 16.

The DS managing unit 18 performs the network maintenance by identifyingequipment within the system 10 that needs replacing, upgrading,repairing, and/or expanding. For example, the DS managing unit 18determines that the DSN memory 22 needs more DS units 36 or that one ormore of the DS units 36 needs updating.

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has a data file 38 and/or data block 40 tostore in the DSN memory 22, it send the data file 38 and/or data block40 to the DS processing unit 16 via its interface 30. As will bedescribed in greater detail with reference to FIG. 2, the interface 30functions to mimic a conventional operating system (OS) file systeminterface (e.g., network file system (NFS), flash file system (FFS),disk file system (DFS), file transfer protocol (FTP), web-baseddistributed authoring and versioning (WebDAV), etc.) and/or a blockmemory interface (e.g., small computer system interface (SCSI), internetsmall computer system interface (iSCSI), etc.). In addition, theinterface 30 may attach a user identification code (ID) to the data file38 and/or data block 40.

The DS processing unit 16 receives the data file 38 and/or data block 40via its interface 30 and performs a distributed storage (DS) process 34thereon (e.g., an error coding dispersal storage function). The DSprocessing 34 begins by partitioning the data file 38 and/or data block40 into one or more data segments, which is represented as Y datasegments. For example, the DS processing 34 may partition the data file38 and/or data block 40 into a fixed byte size segment (e.g., 2¹ to2^(n) bytes, where n=>2) or a variable byte size (e.g., change byte sizefrom segment to segment, or from groups of segments to groups ofsegments, etc.).

For each of the Y data segments, the DS processing 34 error encodes(e.g., forward error correction (FEC), information dispersal algorithm,or error correction coding) and slices (or slices then error encodes)the data segment into a plurality of error coded (EC) data slices 42-48,which is represented as X slices per data segment. The number of slices(X) per segment, which corresponds to a number of pillars n, is set inaccordance with the distributed data storage parameters and the errorcoding scheme. For example, if a Reed-Solomon (or other FEC scheme) isused in an n/k system, then a data segment is divided into n slices,where k number of slices is needed to reconstruct the original data(i.e., k is the threshold). As a few specific examples, the n/k factormay be 5/3; 6/4; 8/6; 8/5; 16/10.

For each slice 42-48, the DS processing unit 16 creates a unique slicename and appends it to the corresponding slice 42-48. The slice nameincludes universal DSN memory addressing routing information (e.g.,virtual memory addresses in the DSN memory 22) and user-specificinformation (e.g., user ID, file name, data block identifier, etc.).

The DS processing unit 16 transmits the plurality of EC slices 42-48 toa plurality of DS units 36 of the DSN memory 22 via the DSN interface 32and the network 24. The DSN interface 32 formats each of the slices fortransmission via the network 24. For example, the DSN interface 32 mayutilize an internet protocol (e.g., TCP/IP, etc.) to packetize theslices 42-48 for transmission via the network 24.

The number of DS units 36 receiving the slices 42-48 is dependent on thedistributed data storage parameters established by the DS managing unit18. For example, the DS managing unit 18 may indicate that each slice isto be stored in a different DS unit 36. As another example, the DSmanaging unit 18 may indicate that like slice numbers of different datasegments are to be stored in the same DS unit 36. For example, the firstslice of each of the data segments is to be stored in a first DS unit36, the second slice of each of the data segments is to be stored in asecond DS unit 36, etc. In this manner, the data is encoded anddistributedly stored at physically diverse locations to improved datastorage integrity and security. Further examples of encoding the datasegments will be provided with reference to one or more of FIGS. 2-19.

Each DS unit 36 that receives a slice 42-48 for storage translates thevirtual DSN memory address of the slice into a local physical addressfor storage. Accordingly, each DS unit 36 maintains a virtual tophysical memory mapping to assist in the storage and retrieval of data.

The first type of user device 12 performs a similar function to storedata in the DSN memory 22 with the exception that it includes the DSprocessing. As such, the device 12 encodes and slices the data fileand/or data block it has to store. The device then transmits the slices11 to the DSN memory via its DSN interface 32 and the network 24.

For a second type of user device 14 to retrieve a data file or datablock from memory, it issues a read command via its interface 30 to theDS processing unit 16. The DS processing unit 16 performs the DSprocessing 34 to identify the DS units 36 storing the slices of the datafile and/or data block based on the read command. The DS processing unit16 may also communicate with the DS managing unit 18 to verify that theuser device 14 is authorized to access the requested data.

Assuming that the user device is authorized to access the requesteddata, the DS processing unit 16 issues slice read commands to at least athreshold number of the DS units 36 storing the requested data (e.g., toat least 10 DS units for a 16/10 error coding scheme). Each of the DSunits 36 receiving the slice read command, verifies the command,accesses its virtual to physical memory mapping, retrieves the requestedslice, or slices, and transmits it to the DS processing unit 16.

Once the DS processing unit 16 has received a read threshold number ofslices for a data segment, it performs an error decoding function andde-slicing to reconstruct the data segment. When Y number of datasegments has been reconstructed, the DS processing unit 16 provides thedata file 38 and/or data block 40 to the user device 14. Note that thefirst type of user device 12 performs a similar process to retrieve adata file and/or data block.

The storage integrity processing unit 20 performs the third primaryfunction of data storage integrity verification. In general, the storageintegrity processing unit 20 periodically retrieves slices 45, and/orslice names, of a data file or data block of a user device to verifythat one or more slices have not been corrupted or lost (e.g., the DSunit failed). The retrieval process mimics the read process previouslydescribed.

If the storage integrity processing unit 20 determines that one or moreslices is corrupted or lost, it rebuilds the corrupted or lost slice(s)in accordance with the error coding scheme. The storage integrityprocessing unit 20 stores the rebuild slice, or slices, in theappropriate DS unit(s) 36 in a manner that mimics the write processpreviously described.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,at least one IO device interface module 62, a read only memory (ROM)basic input output system (BIOS) 64, and one or more memory interfacemodules. The memory interface module(s) includes one or more of auniversal serial bus (USB) interface module 66, a host bus adapter (HBA)interface module 68, a network interface module 70, a flash interfacemodule 72, a hard drive interface module 74, and a DSN interface module76. Note the DSN interface module 76 and/or the network interface module70 may function as the interface 30 of the user device 14 of FIG. 1.Further note that the IO device interface module 62 and/or the memoryinterface modules may be collectively or individually referred to as IOports.

The processing module 50 may be a single processing device or aplurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module 50 may have anassociated memory and/or memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry of theprocessing module 50. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module 50includes more than one processing device, the processing devices may becentrally located (e.g., directly coupled together via a wired and/orwireless bus structure) or may be distributedly located (e.g., cloudcomputing via indirect coupling via a local area network and/or a widearea network). Further note that when the processing module 50implements one or more of its functions via a state machine, analogcircuitry, digital circuitry, and/or logic circuitry, the memory and/ormemory element storing the corresponding operational instructions may beembedded within, or external to, the circuitry comprising the statemachine, analog circuitry, digital circuitry, and/or logic circuitry.Still further note that, the memory element stores, and the processingmodule 50 executes, hard coded and/or operational instructionscorresponding to at least some of the steps and/or functions illustratedin FIGS. 1-19.

FIG. 3 is a schematic block diagram of an embodiment of a dispersedstorage (DS) processing module 34 of user device 12 and/or of the DSprocessing unit 16. The DS processing module 34 includes a gatewaymodule 78, an access module 80, a grid module 82, and a storage module84. The DS processing module 34 may also include an interface 30 and theDSnet interface 32 or the interfaces 68 and/or 70 may be part of user 12or of the DS processing unit 14. The DS processing module 34 may furtherinclude a bypass/feedback path between the storage module 84 to thegateway module 78. Note that the modules 78-84 of the DS processingmodule 34 may be in a single unit or distributed across multiple units.

In an example of storing data, the gateway module 78 receives anincoming data object that includes a user ID field 86, an object namefield 88, and the data field 40 and may also receive correspondinginformation that includes a process identifier (e.g., an internalprocess/application ID), metadata, a file system directory, a blocknumber, a transaction message, a user device identity (ID), a dataobject identifier, a source name, and/or user information. The gatewaymodule 78 authenticates the user associated with the data object byverifying the user ID 86 with the managing unit 18 and/or anotherauthenticating unit.

When the user is authenticated, the gateway module 78 obtains userinformation from the management unit 18, the user device, and/or theother authenticating unit. The user information includes a vaultidentifier, operational parameters, and user attributes (e.g., userdata, billing information, etc.). A vault identifier identifies a vault,which is a virtual memory space that maps to a set of DS storage units36. For example, vault 1 (i.e., user 1's DSN memory space) includeseight DS storage units (X=8 wide) and vault 2 (i.e., user 2's DSN memoryspace) includes sixteen DS storage units (X=16 wide). The operationalparameters may include an error coding algorithm, the width n (number ofpillars X or slices per segment for this vault), a read threshold T, awrite threshold, an encryption algorithm, a slicing parameter, acompression algorithm, an integrity check method, caching settings,parallelism settings, and/or other parameters that may be used to accessthe DSN memory layer.

The gateway module 78 uses the user information to assign a source name35 to the data. For instance, the gateway module 60 determines thesource name 35 of the data object 40 based on the vault identifier andthe data object. For example, the source name may contain a fileidentifier (ID), a vault generation number, a reserved field, and avault identifier (ID). As another example, the gateway module 78 maygenerate the file ID based on a hash function of the data object 40.Note that the gateway module 78 may also perform message conversion,protocol conversion, electrical conversion, optical conversion, accesscontrol, user identification, user information retrieval, trafficmonitoring, statistics generation, configuration, management, and/orsource name determination.

The access module 80 receives the data object 40 and creates a series ofdata segments 1 through Y 90-92 in accordance with a data storageprotocol (e.g., file storage system, a block storage system, and/or anaggregated block storage system). The number of segments Y may be chosenor randomly assigned based on a selected segment size and the size ofthe data object. For example, if the number of segments is chosen to bea fixed number, then the size of the segments varies as a function ofthe size of the data object. For instance, if the data object is animage file of 4,194,304 eight bit bytes (e.g., 33,554,432 bits) and thenumber of segments Y=131,072, then each segment is 256 bits or 32 bytes.As another example, if segment sized is fixed, then the number ofsegments Y varies based on the size of data object. For instance, if thedata object is an image file of 4,194,304 bytes and the fixed size ofeach segment is 4,096 bytes, the then number of segments Y=1,024. Notethat each segment is associated with the same source name.

The grid module 82 receives the data segments and may manipulate (e.g.,compression, encryption, cyclic redundancy check (CRC), etc.) each ofthe data segments before performing an error coding function of theerror coding dispersal storage function to produce a pre-manipulateddata segment. After manipulating a data segment, if applicable, the gridmodule 82 error encodes (e.g., Reed-Solomon, Convolution encoding,Trellis encoding, etc.) the data segment or manipulated data segmentinto X error coded data slices 42-44.

The value X, or the number of pillars (e.g., X=16), is chosen as aparameter of the error coding dispersal storage function. Otherparameters of the error coding dispersal function include a readthreshold T, a write threshold W, etc. The read threshold (e.g., T=10,when X=16) corresponds to the minimum number of error-free error codeddata slices required to reconstruct the data segment. In other words,the DS processing module 34 can compensate for X−T (e.g., 16−10=6)missing error coded data slices per data segment. The write threshold Wcorresponds to a minimum number of DS storage units that acknowledgeproper storage of their respective data slices before the DS processingmodule indicates proper storage of the encoded data segment. Note thatthe write threshold is greater than or equal to the read threshold for agiven number of pillars (X).

For each data slice of a data segment, the grid module 82 generates aunique slice name 37 and attaches it thereto. The slice name 37 includesa universal routing information field and a vault specific field and maybe 48 bytes (e.g., 24 bytes for each of the universal routinginformation field and the vault specific field). As illustrated, theuniversal routing information field includes a slice index, a vault ID,a vault generation, and a reserved field. The slice index is based onthe pillar number and the vault ID and, as such, is unique for eachpillar (e.g., slices of the same pillar for the same vault for anysegment will share the same slice index). The vault specific fieldincludes a data name, which includes a file ID and a segment number(e.g., a sequential numbering of data segments 1-Y of a simple dataobject or a data block number).

Prior to outputting the error coded data slices of a data segment, thegrid module may perform post-slice manipulation on the slices. Ifenabled, the manipulation includes slice level compression, encryption,CRC, addressing, tagging, and/or other manipulation to improve theeffectiveness of the computing system.

When the error coded data slices of a data segment are ready to beoutputted, the grid module 82 determines which of the DS storage units36 will store the EC data slices based on a dispersed storage memorymapping associated with the user's vault and/or DS storage unitattributes. The DS storage unit attributes may include availability,self-selection, performance history, link speed, link latency,ownership, available DSN memory, domain, cost, a prioritization scheme,a centralized selection message from another source, a lookup table,data ownership, and/or any other factor to optimize the operation of thecomputing system. Note that the number of DS storage units 36 is equalto or greater than the number of pillars (e.g., X) so that no more thanone error coded data slice of the same data segment is stored on thesame DS storage unit 36. Further note that EC data slices of the samepillar number but of different segments (e.g., EC data slice 1 of datasegment 1 and EC data slice 1 of data segment 2) may be stored on thesame or different DS storage units 36.

The storage module 84 performs an integrity check on the outboundencoded data slices and, when successful, identifies a plurality of DSstorage units based on information provided by the grid module 82. Thestorage module 84 then outputs the encoded data slices 1 through X ofeach segment 1 through Y to the DS storage units 36. Each of the DSstorage units 36 stores its EC data slice(s) and maintains a localvirtual DSN address to physical location table to convert the virtualDSN address of the EC data slice(s) into physical storage addresses.

In an example of a read operation, the user device 12 and/or 14 sends aread request to the DS processing unit 14, which authenticates therequest. When the request is authentic, the DS processing unit 14 sendsa read message to each of the DS storage units 36 storing slices of thedata object being read. The slices are received via the DSnet interface32 and processed by the storage module 84, which performs a parity checkand provides the slices to the grid module 82 when the parity check wassuccessful. The grid module 82 decodes the slices in accordance with theerror coding dispersal storage function to reconstruct the data segment.The access module 80 reconstructs the data object from the data segmentsand the gateway module 78 formats the data object for transmission tothe user device.

FIG. 4 is a schematic block diagram of an embodiment of a grid module 82that includes a control unit 73, a pre-slice manipulator 75, an encoder77, a slicer 79, a post-slice manipulator 81, a pre-slice de-manipulator83, a decoder 85, a de-slicer 87, and/or a post-slice de-manipulator 89.Note that the control unit 73 may be partially or completely external tothe grid module 82. For example, the control unit 73 may be part of thecomputing core at a remote location, part of a user device, part of theDS managing unit 18, or distributed amongst one or more DS storageunits.

In an example of write operation, the pre-slice manipulator 75 receivesa data segment 90-92 and a write instruction from an authorized userdevice. The pre-slice manipulator 75 determines if pre-manipulation ofthe data segment 90-92 is required and, if so, what type. The pre-slicemanipulator 75 may make the determination independently or based oninstructions from the control unit 73, where the determination is basedon a computing system-wide predetermination, a table lookup, vaultparameters associated with the user identification, the type of data,security requirements, available DSN memory, performance requirements,and/or other metadata.

Once a positive determination is made, the pre-slice manipulator 75manipulates the data segment 90-92 in accordance with the type ofmanipulation. For example, the type of manipulation may be compression(e.g., Lempel-Ziv-Welch, Huffman, Golomb, fractal, wavelet, etc.),signatures (e.g., Digital Signature Algorithm (DSA), Elliptic Curve DSA,Secure Hash Algorithm, etc.), watermarking, tagging, encryption (e.g.,Data Encryption Standard, Advanced Encryption Standard, etc.), addingmetadata (e.g., time/date stamping, user information, file type, etc.),cyclic redundancy check (e.g., CRC32), and/or other data manipulationsto produce the pre-manipulated data segment.

The encoder 77 encodes the pre-manipulated data segment 92 using aforward error correction (FEC) encoder (and/or other type of erasurecoding and/or error coding) to produce an encoded data segment 94. Theencoder 77 determines which forward error correction algorithm to usebased on a predetermination associated with the user's vault, a timebased algorithm, user direction, DS managing unit direction, controlunit direction, as a function of the data type, as a function of thedata segment 92 metadata, and/or any other factor to determine algorithmtype. The forward error correction algorithm may be Golay,Multidimensional parity, Reed-Solomon, Hamming, Bose Ray ChauduriHocquenghem (BCH), Cauchy-Reed-Solomon, or any other FEC encoder. Notethat the encoder 77 may use a different encoding algorithm for each datasegment 92, the same encoding algorithm for the data segments 92 of adata object, or a combination thereof.

The encoded data segment 94 is of greater size than the data segment 92by the overhead rate of the encoding algorithm by a factor of X/T, whereX is the width or number of slices, and T is the read threshold. In thisregard, the corresponding decoding process can accommodate at most X−Tmissing EC data slices and still recreate the data segment 92. Forexample, if X=16 and T=10, then the data segment 92 will be recoverableas long as 10 or more EC data slices per segment are not corrupted.

The slicer 79 transforms the encoded data segment 94 into EC data slicesin accordance with the slicing parameter from the vault for this userand/or data segment 92. For example, if the slicing parameter is X=16,then the slicer 79 slices each encoded data segment 94 into 16 encodedslices.

The post-slice manipulator 81 performs, if enabled, post-manipulation onthe encoded slices to produce the EC data slices. If enabled, thepost-slice manipulator 81 determines the type of post-manipulation,which may be based on a computing system-wide predetermination,parameters in the vault for this user, a table lookup, the useridentification, the type of data, security requirements, available DSNmemory, performance requirements, control unit directed, and/or othermetadata. Note that the type of post-slice manipulation may includeslice level compression, signatures, encryption, CRC, addressing,watermarking, tagging, adding metadata, and/or other manipulation toimprove the effectiveness of the computing system.

In an example of a read operation, the post-slice de-manipulator 89receives at least a read threshold number of EC data slices and performsthe inverse function of the post-slice manipulator 81 to produce aplurality of encoded slices. The de-slicer 87 de-slices the encodedslices to produce an encoded data segment 94. The decoder 85 performsthe inverse function of the encoder 77 to recapture the data segment90-92. The pre-slice de-manipulator 83 performs the inverse function ofthe pre-slice manipulator 75 to recapture the data segment 90-92.

FIG. 5 is a diagram of an example of slicing an encoded data segment 94by the slicer 79. In this example, the encoded data segment 94 includesthirty-two bits, but may include more or less bits. The slicer 79disperses the bits of the encoded data segment 94 across the EC dataslices in a pattern as shown. As such, each EC data slice does notinclude consecutive bits of the data segment 94 reducing the impact ofconsecutive bit failures on data recovery. For example, if EC data slice2 (which includes bits 1, 5, 9, 13, 17, 25, and 29) is unavailable(e.g., lost, inaccessible, or corrupted), the data segment can bereconstructed from the other EC data slices (e.g., 1, 3 and 4 for a readthreshold of 3 and a width of 4).

FIG. 6 is a flowchart illustrating an example of managing a memorydevice. The method begins with step 102 where a processing moduledetermines whether a memory device of a dispersed storage (DS) unit isunavailable to produce an unavailable memory device. Such adetermination may be based on one or more of a query, an indicator thatthe memory device has been physically removed, an error message, aplurality of error messages, a power indicator, a command, a message,and a failure indicator.

When the memory device is unavailable, the method continues at step 104where the processing module determines a methodology regarding DSencoded data stored in the unavailable memory device based on one ormore dispersed storage network (DSN) conditions to produce a determinedmethodology. Such one or more DSN conditions includes at least one of adecode threshold and pillar width ratio, a number of DS units in a vaultthat are unavailable, network traffic, and a priority level of the DSencoded data. Such a methodology includes waiting for the unavailablememory device to become available again (e.g., repaired) and rebuildingthe DS encoded data after a time period to produce rebuilt DS encodeddata and storing the rebuilt DS encoded data in one or more otheravailable memory devices (e.g., a hot-standby memory device and/or aplurality of portions of a plurality of other memory devices of theavailable memory devices). The method continues to step 106 when thedetermined methodology includes waiting for the memory device to becomeavailable. The method branches to step 110 when the determinedmethodology includes a rebuilding component.

The method continues at step 106 where the processing module waits forthe memory device to become available by determining whether theunavailable memory device is now available when the determinedmethodology includes waiting for the memory device to become available.The method repeats to step 106 when the processing module determinesthat the unavailable memory device is not available. The methodcontinues to step 108 when the processing module determines that theunavailable memory is now available. The method continues at step 108where the processing module changes the status of the memory device fromunavailable to available when the unavailable memory device becomesavailable.

The method continues at step 110 where the processing module establishesa time period based on the one or more DSN conditions when thedetermined methodology includes the rebuilding component and determineswhether the time period expires. For example, the processing moduleestablishes the time period to be two days in accordance with thedetermined methodology, including avoiding utilizing network bandwidthto rebuild the DS encoded data. The method repeats to step 110 when theprocessing module determines that the time period has not expired. Themethod continues to step 112 when the processing module determines thetime period has expired.

The method continues at step 112 where the processing module determinesa memory type to utilize by determining whether a DS unit includes ahot-standby memory device. Such a determination may be based on one ormore of a query, a message, a registry, a list, a lookup, a command, anda request. When the DS unit includes the hot-standby memory device, theprocessing module determines, in accordance with the determinedmethodology, whether to use the hot-standby memory device, whereinavailable memory of the DS unit includes the hot-standby memory device.The method branches to step 118 when the processing module determines toutilize available memory (e.g., other than the hot-standby memorydevice). The method continues to step 114 when the processing moduledetermines to utilize the hot-standby memory device.

The method continues at step 114 where the processing module reassigns aslice name range associated with the unavailable memory device to thehot-standby memory device prior to the storing rebuilt DS encoded datawhen the hot-standby memory device is to be used. Such reassigning ofthe slice name range includes updating the slice name range in a memorydevice table from the unavailable memory device to the hot-standbymemory device.

The method continues at step 116 where the processing module initiates,in accordance with the determined methodology, a rebuilding function torebuild the DS encoded data to produce rebuilt DS encoded data andstoring the rebuilt DS encoded data within the hot-standby memory deviceof the DS unit. Such a rebuilding function may include at least one ofexecuting the rebuilding function to rebuild the DS encoded data andrequesting execution of the rebuilding function to rebuild the DSencoded data (e.g., sending a rebuilding request message to at least oneof a storage integrity processing unit, a DS processing unit, and a DSunit).

The method continues to step 118 where the processing module reassignsthe slice name range associated with the unavailable memory device tothe available memory of the DS unit prior to the storing the rebuilt DSencoded data when the available memory is to be used. Such reassigningof the slice name range includes at least one of updating the slice namerange in the memory device table from the unavailable memory device tothe available memory of the DS unit and when the available memory of theDS unit includes a plurality of memory devices, partitioning the slicename range into a plurality of slice name range partitions and assigningone of the plurality of slice name range partitions to one of theplurality of memory devices and updating a status indicator of theunavailable memory (e.g., changing a status from assigned to anassigned). Such partitioning of the slice name ranges may be based onone or more of slice name address range indicators for the plurality ofmemory devices, available capacity indicators for the plurality ofmemory devices, a slice redistribution policy, a slice storagerequirement, a performance indicator, a security indicator, a priorityindicator, and an estimation of performance.

The method continues at step 120 where the processing module initiatesthe rebuilding function and stores the rebuilt DS encoded data withinavailable memory of the DS unit. The method continues at step 122 wherethe processing module determines whether to transfer the rebuilt DSencoded data from the available memory of the DS unit to an additionalmemory of the DS unit. Such additional memory of the DS unit may includeat least one of refurbished memory and new memory. Such a determinationmay be based on one or more of a memory capacity indicator associatedwith the additional memory, a performance indicator associated with theadditional memory, a message, a request, and a command. For example, theprocessing module determines to transfer the rebuilt DS encoded datafrom the available memory to the additional memory when a new memory isdetected and a capacity indicator associated with the new memorycompares favorably to an amount of rebuilt DS encoded data. The methodrepeats back to step 122 when the processing module determines to nottransfer the rebuilt DS encoded data. The method continues to step 124when the processing module determines to transfer the rebuilt DS encodeddata.

The method continues at step 124 where the processing module reassigns aslice name range associated with the available memory of the DS unit tothe additional memory when the rebuilt DS encoded data is to betransferred from the available memory of the DS unit to the additionalmemory. The method continues at step 126 where the processing moduletransfers the rebuilt DS encoded data from the available memory of theDS unit to the additional memory. In addition, the processing module maydelete the rebuilt DS encoded data from the available memory when therebuilt DS encoded data is successfully stored in the additional memory.

FIG. 7 A is a flowchart illustrating an example of authorizing an accessrequest. The method begins with step 136 where a processing modulereceives an access request. Such an access request may include one ormore of a user identifier (ID), an access type (e.g., read, write,delete, list, list range, check, etc.), a user password, a user realmindicator, a command, a data object name, a data object, a virtualdispersed storage network (DSN) address, a performance indicator, apriority indicator, a security indicator, access request requirements, avault ID, a DSN system element access request, a DSN resource request, avault access request, and a record access request. The processing modulemay receive the access request from one or more of a user device, thedispersed storage (DS) processing unit, a storage integrity processingunit, a DS managing unit, and a DS unit.

The method continues at step 138 where the processing module determinesthe realm. Such a realm indicates an affiliation of one or more userdevices/users. For example, the realm indicates a group associated witha particular organization (e.g., a company, a team, a family, a workgroup, a social group, a community, a geographic region, etc.). Such adetermination of the realm may be based on one or more of userinformation, realm information, an authorization table lookup, areceived realm indicator, a user ID, a user password, a vault lookup, atable lookup, and any other information from the access request.

The method continues at step 140 where the processing module determinesan authorization service. Such an authorization service indicates anidentity and/or address to provide subsequent authorization of theaccess request. For example, the processing module identifies theauthorization service to include a third-party, which may or may not bepart of the DSN computing system. Such a third-party may provideauthorization information (e.g., if a user or group is allowed toperform a particular type of DSN computing system access). Such adetermination of the authorization service may be based on one or moreof information associated with the realm, an authorization table lookup,a vault lookup, a user ID, a user password, and information received inthe access request.

The method continues at step 142 where the processing module generatesan authorization request and sends the authorization request to theauthorization service. Such an authorization request may include one ormore of the user ID, a user password, user information, the user realminformation, a command, the data object name, a virtual DSN address, anda DS processing module ID. The method continues at step 144 where theprocessing module receives an authorization request response from theauthorization service. The method continues at step 146 where theprocessing module determines whether the request is authorized based onthe authorization request response. The method ends at step 148 wherethe processing module sends a reject message when the processing moduledetermines that the request is not authorized. The processing module maysend the reject message to the requester and/or the DS managing unit.The method continues to step 150 when the processing module determinesthat the request is authorized. The method continues at step 150 wherethe processing module processes the access request (e.g., processes acommand including store, retrieve, delete, list, etc.).

FIG. 7 B is a diagram illustrating an example of an authorization table152. Such an authorization table 152 may be utilized by a processingmodule to determine an authorization service based on user informationas discussed with reference to the method of FIG. 7 A. Such anauthorization table 152 may be stored in one or more of a dispersedstorage (DS) unit, a DS managing unit, a storage integrity processingunit, a user device, and a DS processing unit. In an example, the DSmanaging unit generates the authorization table 152 and sends theinformation of the authorization table 152 to the DS unit for storageand ongoing use to authorize access requests.

Such an authorization table and 52 includes a user information field154, a realm field 156, and an authorization service field 158. The userinformation field 154 includes identities of one or more users and/oruser devices associated, wherein each user is associated with aparticular realm. For example, an e-mail address may be utilized touniquely identify a user and/or user device. The realm field 156includes group identities associated with the one or more users. Forexample, a realm entry identifies a domain of an e-mail address suchthat a shared affiliation is a common e-mail domain (e.g., a company, anorganization, etc.). The authorization service field 158 includes anidentity and address of an associated authorization servicecorresponding to a realm. For example, an entry of the authorizationservice field 158 indicates an Internet address that may be utilized tosend an authorization request to and receive a correspondingauthorization request response.

In an example of operation, an e-mail address of joew@cleversafe.com isutilized to index into the authorization table 152 by matching e-mailaddress to an entry of the user information field 154. An associatedrealm of cleversafe.com is extracted from the realm field 156 based on acorresponding e-mail address entry matched to an entry of the associatedrealm. Next, an authorization service address of ldaps.cleversafe.com isextracted from the authorization service field 158 based on thecorresponding e-mail address entry matched to an entry of the associatedauthorization service. An access request authorization message is sentto the ldaps.cleversafe.com address to determine whether an associatedaccess request is authorized.

FIG. 8 A is a diagram illustrating an example of a memory utilizationmap sequence that includes a sequence of memory utilization map states162-166. Each memory utilization map state of the memory utilization mapstates 162-166 represents a memory utilization level 160 (e.g., 0, 1, 2,3, 4 terabytes (TB)) of a plurality of memory devices 1-4 correspondingto a state of memory utilization of the sequence of memory utilizationmap states 162-166. Such memory devices 1-4 include memory devices(e.g., Flash memory, random access memory, magnetic disk drive memory,etc.) within one of a common dispersed storage (DS) unit and two or moreDS units. For example, memory devices 1-4 are implemented in DS unit 1.In another example, memory devices 1-2 are implemented in DS unit 1 andmemory devices 3-4 are implemented in DS unit 2. As yet another example,memory device 1 is implemented in DS unit 1, memory device 2 isimplemented in DS unit 2, memory device 3 is implemented in DS unit 3,and memory device 4 is implemented in DS unit 4.

Encoded data slices corresponding to a slice name range 161 (e.g.,125-185) are stored in the memory devices 1-4 in accordance with slicename ranges associated with each memory device of the memory devices1-4. Such a slice name range 161 includes (m−1) address boundaries toform the slice name ranges associated with each memory device of thememory devices 1-4, wherein m=a number of memory devices 1-4. Forinstance, 3 address boundaries form the slice name ranges associatedwith each memory device when there are 4 memory devices. Such addressboundaries may be determined based on one or more of a memory balancingfunction, a memory balancing goal, an impact threshold, a memoryutilization map state, previous address boundaries, a number of memorydevices, a memory utilization level of each of the memory devices 1-4(e.g., the utilization level rises as more encoded data slices arestored), and the slice name range 125-185.

Such a sequence of memory utilization map states 162-166 may correspondto an initial state 162, a balanced state 166, and one or moreintermediate states 163-165. Such an initial state 162 represents amemory utilization map state when memory devices 1-4 are initiallyassigned to the slice name range 161 (e.g., memory devices 1-4 areunutilized and assigned). Such a balanced state 166 represents a memoryutilization map state when memory devices 1-4 are utilized and balancedas a result of applying the memory balancing function. Such intermediatestates 163-165 includes an unbalanced state 163 and may include one ormore intermediate steps (e.g., step 1 state 164, step 2 state 165) inapplication of the memory balancing function to transition the memorydevices 1-4 from the unbalanced state 163 to the balanced state 166).Such an unbalanced state 163 represents a memory utilization map statewhen memory devices 1-4 are utilized and unbalanced as a result ofstoring encoded data slices in accordance with address boundariesassociated with the initial state 162.

Such a memory balancing function results in a memory utilization levelof each memory device of the memory devices 1-4 being substantially thesame (e.g., balanced state 166). Such a memory balancing function may beapplied to the memory devices 1-4 by modifying the address boundariesassociated with the address range 161 to produce modified slice nameranges of at least two the memory devices 1-4 and transferring encodeddata slices from one memory device to another memory device inaccordance with the modified slice name ranges. The memory balancingfunction may be applied in one or more steps to transition from theunbalanced state 163 to the memory state 166.

In an example of operation, address boundaries of 140, 155, and 170 formslice name ranges for each memory device of memory devices 1-4, when thememory devices 1-4 are assigned in the initial state 162. For instance,encoded data slices corresponding to a slice name range of 125-140 arestored in memory device 1, encoded data slices corresponding to a slicename range of 140-155 are stored in memory device 2, encoded data slicescorresponding to a slice name range of 155-170 are stored in memorydevice 3, and encoded data slices corresponding to a slice name range of170-185 are stored in memory device 4. Encoded data slices are stored inthe memory devices 1-4 in accordance with the slice name ranges of eachof the memory devices 1-4. For instance, 4 TB of encoded data slices arestored in memory device 1, 2 TB of encoded data slices are stored inmemory device 2, 1 TB of encoded data slices are stored in memory device3, and 3 TB of encoded data slices are stored in memory device 4 whenthe memory utilization map produces the unbalanced state 163.

In the example of operation continued, the memory balancing function isapplied such that an address boundary between memory device 3 and memorydevice 4 is modified from 170 to 175 to produce a modified slice namerange of 155-175 for memory device 3 and a modified slice name range of175-185 for memory device 4. Encoded data slices associated with slicename addresses 170-175 are transferred from memory device 4 to memorydevice 3 such that memory device 3 and memory device 4 are eachassociated with a utilization level of 2 TB. Such an encoded data slicetransfer and modified slice name ranges results in step 1 state 164.

Continuing with the example of operation, the memory balancing functionis applied such that an address boundary between memory device 1 andmemory device 2 is modified from 140 to 135 to produce a modified slicename range of 125-135 for memory device 1 and a modified slice namerange of 135-155 for memory device 2. Encoded data slices associatedwith slice name addresses 135-140 are transferred from memory device 1to memory device 2 such that memory device 1 and memory device 2 areeach associated with a utilization level of 3 TB. Such an encoded dataslice transfer and modified slice name ranges results in step 2 state165. Next, the memory balancing function is further applied and mayinclude more steps resulting in more intermediate states to reach thebalanced state 166 where each memory device is associated with autilization level of 2.5 TB.

In another example of operation, the memory balancing function isapplied to the memory devices in the unbalanced state 163 to movedirectly to the balanced state 166 (e.g., without moving through one ormore intermediate states 164-165). The method of operation of thebalancing function is discussed in greater detail with reference to FIG.8 B.

FIG. 8 B is a flowchart illustrating an example of balancing memoryutilization. The method begins with step 168 where processing moduleidentifies a memory loading mismatch between two or more memory devicesof a plurality of memory devices of a dispersed storage (DS) unit,wherein each of the plurality of memory devices is assigned a range ofslice names to provide a plurality of assigned ranges of slice names.For example, processing module identifies a memory loading mismatchbetween a first memory device and a second memory device of the DS unit,wherein the first memory device is assigned a first range of slice namesand the second memory device is assigned a second range of slice names.

Such identifying of the memory loading mismatch includes at least one ofdetermining a utilized amount of storage for each of the plurality ofmemory devices (e.g., based on one or more of a query, a list, a ping, amessage, a command, an error message, and a lookup), determining anunutilized amount of storage for each of the plurality of memorydevices, determining a utilization percentage of storage capacity foreach of the plurality of memory devices, determining an unutilizedpercentage of storage capacity for each of the plurality of memorydevices, and determining a storage balancing factor for a group ofencoded data slices associated with at least one of a priorityindicator, a security indicator, a performance indicator, a useridentifier, and a vault identifier. Alternatively, or addition to, suchidentifying of the memory loading mismatch includes at least one ofdetermining a utilized amount of storage for each of the first andsecond memory devices, determining an unutilized amount of storage foreach of the first and second memory devices, determining a utilizationpercentage of storage capacity for each of the first and second memorydevices, and determining an unutilized percentage of storage capacityfor each of the first and second memory devices when the memory loadingmismatch is to be identified between the first memory device and thesecond memory device.

The method continues at step 170 where the processing module determinesan estimated impact to reduce the memory loading mismatch. Suchdetermining of the estimated impact comprises at least one ofdetermining a financial impact based on one or more of a cost level anda revenue gain/loss level, determining a processing resource impactbased on one or more of a memory capacity extension time period, abalancing execution time period, a performance level, a wide areanetwork bandwidth utilization level to execute load balancing, and alocal area network bandwidth utilization level to execute the loadbalancing, determining an accessibility impact based on one or more of awide area network bandwidth availability level, a local area networkbandwidth availability level, a memory unavailability time period, andbalancing execution time, and determining a user impact based on one ormore of a security level, a priority level, an associated useridentifier (ID), and an associated vault ID.

The method continues at step 172 where the processing module determineswhether the estimated impact compares favorably to an impact threshold.For example, the processing module determines that the estimated impactcompares favorably to the impact threshold when the balancing executiontime is less than the impact threshold. As another example, theprocessing module determines that the estimated impact comparesfavorably to the impact threshold when the revenue gain is greater thanthe impact threshold. The method repeats back to step 168 when theprocessing module determines that the estimated impact comparesunfavorably to the impact threshold. The method continues to step 174when the processing module determines that the estimated impact comparesfavorably to the impact threshold.

The method continues at step 174 where the processing module modifies atleast two of the plurality of assigned ranges of slices names to producea modified plurality of assigned ranges of slice names for the pluralityof memory devices based on the memory loading mismatch when theestimated impact compares favorably to an impact threshold. For example,processing module modifies the first and second ranges of slices namesto produce a first modified range of slice names for the first memorydevice and a second modified range of slice names for the second memorydevice based on the memory loading mismatch.

Such modifying of the at least two of the plurality of assigned rangesof slices names includes de-assigning a first range of slice names froma first memory device of the at least two memory devices and a secondrange of slice names from a second memory device of the at least twomemory devices to create an unassigned range of slice names andpartitioning the unassigned range of slices names to approximatelybalance (e.g., same utilization level) loading of the first and secondmemory devices to produce the modified plurality of assigned ranges ofslice names. For example, the processing module modifies the first andsecond ranges of slice names to include de-assigning the first andsecond ranges of slice names from the first and second memory devices tocreate the unassigned range of slice names and partitioning theunassigned range of slices names to approximately balance loading of thefirst and second memory devices to produce first and second modifiedranges of slice names.

The method continues at step 176 where the processing module transfersone or more encoded data slices between two or more memory devices ofthe plurality of memory devices in accordance with the modifiedplurality of assigned ranges of slice names. Alternatively, or inaddition to, the processing module transfers one or more encoded dataslices between the first and second memory devices in accordance withthe first and second modified ranges of slice names.

FIG. 9 A is a flowchart illustrating an example of managing memoryusage. The method begins with step 178 where a processing modulereceives usage information for a vault. Such usage information pertainsto one or more users and/or user devices associated with the vault andmay include one or more of a utilization storage volume, a utilizationpercentage of allocated storage, a utilization percentage of allstorage, and a utilization comparison to at least one other vault. Theprocessing module may receive the usage information from one or more ofa dispersed storage (DS) unit, a user device, a storage integrityprocessing unit, a DS processing unit, and a DS managing unit. Theprocessing module receives the usage information based on one or more ofa response to a query, as an unsolicited message, from time to time,subsequent to a dispersed storage network (DSN) memory access, and acommand from a DS managing unit. For example, the processing modulesends a query to DS units 1-5 and receives the utilization storagevolume usage information for vault 102 from DS units 1-5 of a DS unitstorage set assigned to vault 102.

The method continues at step 180 where the processing module aggregatesthe usage information to produce aggregated usage information based onone or more of user device identifier (ID), a user ID, a vault ID, apredefined group, a realm, a geography, a DS unit storage set, and a DSunit. For example, the processing module aggregates the usageinformation from DS units 1-5 for vault 102 to produce aggregated usageinformation corresponding to vault 102.

The method continues at step 182 where the processing module sends atleast one of the usage information and the aggregated usage informationto one or more of a user device, a DS processing unit, a storageintegrity processing unit, a DS unit, and a DS managing unit. Forexample, the processing module sends aggregated usage information touser device 457 when user device 457 is affiliated with vault 102. Themethod continues at step 184 where the processing module determineswhether the aggregated usage information for user device 457 comparesfavorably to a hard quota. Such a hard quota may specify a usageinformation value such that action is required (e.g., preventingincremental storage usage). The processing module may obtain the hardquota based on one or more of a vault lookup, a hard quota list, apredetermination, DSN memory usage information, a dynamic value based inpart on overall DSN memory usage information, an error message, and acommand. For example, the comparison is favorable when the aggregatedusage information (e.g., 2 terabytes) is less than the hard quota (e.g.,5 terabytes). The method repeats back to step 178 when the processingmodule determines that the usage information compares favorably to thehard quota. The method continues to step 186 when the processing moduledetermines that the usage information compares unfavorably to the hardquota.

The method continues with step 186 where the processing module disableswrite permissions for the corresponding vault. Such disabling of writepermissions curtails further usage of the DSN memory storage facilities.Such disabling of the write permissions may be executed by one or moreof a registry update, a user vault update, a table update, sending amessage to the DS managing unit, and sending a message to the userdevice. The method continues at step 188 where the processing modulesends a write permissions message to one or more DS units affiliatedwith the vault. Such write permissions message may include one or moreof a vault ID, one or more user device IDs, one or more user IDs, amessage indicating that the write permissions are disabled for the vaultID, aggregated usage information, and usage information.

Alternatively, or in addition to, processing module may from time totime re-determine if the usage information compares favorably to thehard quota. Next, the processing module enables the write permissionsfor the vault when the comparison is favorable. For example, encodeddata slices corresponding to the vault are deleted enabling thecomparison to be favorable when the hard quota is substantially the sameas a previous hard quota. In another example, a value associated withthe hard quota is raised enabling the comparison to be favorable.

FIG. 9 B is a flowchart illustrating another example of managing memoryusage. The method begins with step 190 where a processing moduledetermines to store data. For example, the processing module determinesto store a data object. As another example, the processing moduledetermines to store an encoded data slice. Such a determination to storedata may be based on one or more of a user input, a storage algorithm,an application output, a message, a predetermination, and a command.

The method continues at step 192 where the processing module determinesusage information. Such a determination may be based on one or more ofretrieving locally stored usage information, retrieval from a dispersedstorage (DS) processing unit, retrieval from a DS managing unit, aquery, a message, and command. For example, the processing module savesusage information locally (e.g., within a user device). For instance,the processing module retrieves locally stored usage information todetermine that the user device has stored 1.5 terabytes of data so farin a dispersed storage network (DSN) memory.

The method continues at step 194 where the processing module determineswhether the usage information compares favorably to a soft quota. Such asoft quota may specify a usage information value such that action isrequired (e.g., preventing incremental storage usage). The processingmodule may obtain the soft quota based on one or more of a vault lookup,a soft quota list, a predetermination, DSN memory usage information, adynamic value based in part on overall DSN memory usage information, anerror message, and a command. For example, the processing moduledetermines that the usage information compares unfavorably to the softquota when the usage information includes 1.5 terabytes of storageutilization and the soft quota is 1.0 terabytes.

The method branches to step 198 when the processing module determinesthat the usage information compares favorably to the soft quota. Themethod ends at step 196 where the processing module rejects the storeoperation when the processing module determines that the usageinformation compares unfavorably to the soft quota. Such rejecting ofthe store operation includes one or more of sending a message to arequester, sending a message to a DS managing unit, sending a message toa DS processing unit, and preventing further store operations until thecomparison is favorable. The method continues at step 198 where theprocessing module sends data to store when the processing moduledetermines that the usage information compares favorably to the softquota. For example, the processing module sends the data object to a DSprocessing unit for storage in a DSN memory.

FIG. 9 C is a flowchart illustrating another example of managing memoryusage. The method begins with step 200 where a processing modulereceives a write slice request (e.g., a request to store a slice). Sucha write slice request may include one or more of a vault identifier(ID), a user ID, a source name, a slice name, a write command, apriority indicator, a performance indicator, a security indicator, andan encoded data slice. The processing module may receive the write slicerequest from one or more of a user device, a dispersed storage (DS)processing unit, a storage integrity processing unit, a DS managing unitand another DS unit.

The method continues at step 202 where the processing module determineswhether an associated vault of the write slice request is allowed writepermissions. Such a determination may be based on one or more of areceived vault ID, a write permissions table lookup utilizing the vaultID as an index, a user ID, a source name, a slice name, an encoded dataslice, a priority indicator, a performance indicator, a securityindicator, a message, a query, and a command. For example, theprocessing module determines the write permission is not allowed basedon the write permissions table lookup for vault 102 when a write slicerequest is associated with the vault 102. The method branches to step206 when the processing module determines that the vault is allowedwrite permissions. The method continues to step 204 when the processingmodule determines that the vault is not allowed write permissions.

The method continues at step 204 where the processing module rejects thewrite slice request when the processing module determines that the writepermission is not allowed. Such rejecting of the write slice requestincludes one or more of sending a message to a requester, sending amessage to a DS managing unit, sending a message to a DS processingunit, and preventing further processing of write slice requests for thisvault. The method continues at step 206 where the processing moduleprocesses the write slice request (e.g., storing an associated encodeddata slice in memory) when the processing module determines that thevault is allowed write permissions.

FIG. 10 A is a diagram illustrating an example of a user role table 208that may be utilized to stratify dispersed storage network (DSN) systemusers into roles for authorization purposes. Such a user role table 208includes a user field 210 and a role field 212. The user field 210 andthe role field 212 may include any number of entries. Such an entry ofthe user field 210 may be associated with two or more different entriesof the role field 212. Such an entry of the role field 212 may beassociated with two or more different entries of the user field 210.Such entries of the user field 210 include identifiers to identify oneor more of a user, a user device, a dispersed storage (DS) processingmodule, a storage integrity processing unit, a DS managing unit, and aDS unit. Such entries of the role field 212 include level identifiers toidentify predetermined authorized roles with respect to operation of theDSN system.

The user role table 208 may be utilized by one or more of a user device,a DS processing unit, a storage integrity processing unit, a DS managingunit, and a DS unit to determine a role of a user with respect to theDSN system. For example, a processing module of a DS processing unit mayreceive a request from user 831 to access contents of a vault. Theprocessing module determines the role of user 831 to be a vault userbased on a lookup of the user role table 208 utilizing user 831 as anindex.

FIG. 10 B is a diagram illustrating an example of a role permissionstable 214 that may be utilized to determine permissions forauthorization purposes. Such a role permissions table 214 includes arole field 212 and a permissions field 216. The role field is aspreviously described with reference to FIG. 10 A, wherein an entry ofthe role field 212 is associated with an entry of the permissions field216. Such a permissions field 216 includes any number of permissionsentries, wherein each permissions entry indicates permitted activitiesassociated with a corresponding role entry of the role field 212. Such apermissions entry of the permissions entries may be associated with twoor more different entries of the role field 212.

Such a permissions entry of the permissions field 216 indicatespermitted activities for a corresponding role entry of the role field212. Alternatively, or in addition to, the permissions entry of thepermissions field 216 indicates non-permitted activities for thecorresponding role entry of the role field 212. For example, the rolepermissions table 214 indicates that a super user role does not havepermissions to write to or read from a vault but does have permissionsto execute any other operations except for writing and reading to andfrom a vault. As another example, the role permissions table 214indicates that a system administrator role as permissions to read andwrite from any vault, perform account management operations (e.g.,activating users, activating vaults, billing, usage summary generation),but does not have permissions to perform any security operations (e.g.,change security parameters such as which user has access to what data,security policies, network element activation, permissions). As yetanother example, the role permissions table 214 indicates that asecurity officer role has permissions to perform security accountmanager operations. As a further example, the role permissions table 214indicates that an operator role has permissions to execute performancemonitoring functions (e.g., an operator of the DSN system may monitorthe performance and utilization of the DSN system including encoded dataslice retrieval monitoring, activity monitoring, throughput, failures,resource utilization, network use, central processing unit use, deviceload etc.). As yet a further example, the role permissions table 214indicates that a vault user role has permissions to read from and/orwrite to a vault with no other allowed permissions. The method ofutilization of the user role table 208 and the role permissions table214 is discussed in greater detail with reference to FIG. 10 C.

FIG. 10 C is a flowchart illustrating another example of authorizing anaccess request, which includes some of steps to 7 A. The method beginswith step 136 of FIG. 7 A where a processing module receives an accessrequest. The method continues at step 220 where the processing moduledetermines a user identifier (ID) associated with the access request.Such a determination may be based on one or more of a received useridentifier (ID), a vault ID, information contained in the request, avault lookup, a table lookup, a predetermination, a message, a message,and a command.

The method continues at step 222 where the processing module determinesa role associated with the user ID. Such a determination may be based onone or more of the user ID, a user role table lookup, informationreceived, a request, a message, a query, a vault lookup, apredetermination, and command. For example, the processing moduledetermines the role to be a security officer when the processing moduleutilizes a received user ID of 236 as an index to lookup the role in theuser role table.

The method continues at step 224 where the processing module determinespermissions associated with the role. Such a determination may be basedon one or more of the user ID, a vault ID, information contained in therequest, the role, a role permissions table lookup, a query, a vaultlookup, a table lookup, a predetermination, and a command. For example,the processing module determines the permissions to include securityaccount manager functions when the processing module utilizes thesecurity officer role as an index to lookup the permissions in the rolepermissions table lookup.

The method continues at step 226 where the processing module determineswhether the user ID is allowed to perform access request actionsassociated with the access request. Such a determination may be based ona comparison of the request to the permissions. For example, theprocessing module determines that the user is allowed when theprocessing compares a security record access request to the determinedsecurity account manager permissions. As another example, the processingmodule determines that the user is not allowed when the processingcompares a security record access request to a determined vault writerequest. The method branches to step 230 when the processing moduledetermines that the user ID is allowed. The method continues to step 228when the processing module determines that the user ID is not allowed.

The method continues at step 228 where the processing module rejects therequest when the processing module determines that the user is notallowed. Such rejecting of the request includes sending a reject messageto one or more of a user device, a DS managing unit, a DS processingunit, a storage integrity processing unit, and a DS unit. Such a rejectmessage includes access request information based on the access requestand a reject status indicator. The method continues at step 230 wherethe processing module processes the access request (e.g., allowingaccess to DSN system resources) when the processing module determinesthat the user ID is allowed.

FIG. 11 is a flowchart illustrating an example of retrieving data. Themethod begins with step 232 where processing module receives a retrievedata message from a requester to retrieve data (e.g., a user device, adispersed storage (DS) processing module, a storage integrity processingunit, a DS managing unit, and a DS unit). Such a retrieve data messagemay include one or more of a user identifier (ID), a user device ID, arequest code, a date ID, a data object name, a data file name, a sourcename, a data type indicator, a data object hash, a vault ID, a data sizeindicator, a performance indicator, a priority indicator, a securityindicator, a storage requirement, a consistency requirement, and aretrieval threshold requirement.

The method continues at step 234 where the processing module determinesDS unit storage set of a dispersed storage network (DSN), wherein the DSunit storage set stores a plurality of sets of encoded data slicescorresponding to the data. Such a determination may be based on one ormore of information received in the retrieve data message, metadataassociated with the data, a message, a predetermination, and a virtualDSN address to physical location table lookup. For example, theprocessing module determines at least one set of slice names associatedwith the data based on the user ID, the vault ID, and the data ID. Next,the processing module looks up identifiers associated with the DS unitstorage set in the virtual DSN address to physical location table basedon the at least one set of slice names.

At step 234, the processing module determines error coding dispersalstorage function parameters. Such parameters of the error codingdispersal storage function parameters includes a pillar width, a writethreshold, a consistency threshold, a special threshold, a readthreshold, a preliminary retrieval threshold, a retrieval threshold, aread threshold, and a decode threshold. Such a determination may bebased on one or more of information received in the retrieve datamessage, the DS unit storage set, a vault lookup, a command, a message,and a predetermination. A set of encoded slices may include two or moregroups of encoded data slices, wherein each group of the one or moregroups of encoded data slices is associated with a decode thresholdnumber of the encode data slices of a common revision level when thepillar width is at least twice the decode threshold.

The processing module may retrieve and decode the two or more groups ofencoded data slices to produce two or more different data segmentsassociated with a set of encoded data. For example, the processingmodule retrieves and decodes a first group of encoded data slices of theset of encoded data slices from DS units 1-5 to produce a first datasegment and retrieves and decodes a second group of encoded data slicesof the set of encoded data slices from DS units 6-10 to produce a seconddata segment when the pillar width n=10 and the decode threshold k=5. Inan instance, the first data segment and the second data segment aresubstantially the same when the first group of encoded data slices andthe second group of encoded data slices are associated with a commonrevision level. In another instance, the first data segment and thesecond data segment are not substantially the same when the first groupof encoded data slices are associated with a first revision level andthe second group of encoded data slices are associated with a secondrevision level that is different than the first revision level.

The method continues at step 236 where the processing module determinesa retrieval threshold for retrieving a set of encoded data slices fromDSN, wherein the set of encoded data slices represents data (e.g., adata segment) encoded using a dispersed storage error encoding functionhaving a pillar width of “n”, a decode threshold of “k”, and an encodingratio of n−k>k and wherein the retrieval threshold is in accordance withthe encoding ratio. Such determining of the retrieval threshold includesdetermining whether at least a write threshold number of the set ofencoded data slices have a desired revision level. Such a desiredrevision level includes at least one of a most recent revision level, apredetermined revision level, a requested revision level, and a revisionlevel associated with one or more recent favorable write commit responsemessages. For example, the processing module determines that at least awrite threshold number of the set of encoded data slices have a mostrecent revision level of 457 when one or more recent favorable writecommit response messages indicate the at least the write thresholdnumber of encoded data slices associated with revision level 457 weresuccessfully stored in the DS unit storage set.

At step 236, the processing module establishes the retrieval thresholdbased on the pillar width, the write threshold, and a first constantwhen the at least the write threshold number of the set of encoded dataslices have the desired revision level. For example, the processingmodule determines the retrieval threshold in accordance with the formularetrieval threshold=n−WT+1. For instance, the processing moduleestablishes the retrieval threshold to be 16 when the pillar width is30, the write threshold is 15, and the first constant is 1. Suchestablishing of the retrieval threshold may provide a system improvementby eliminating the possibility that another group of a write thresholdnumber of encoded data slices exists in the DS unit storage set, whereinthe another group of the read threshold number of encoded data slicesare associated with a common revision level and are unavailable (e.g.,DS unit off-line, a network failure).

At step 236, the processing module establishes the retrieval thresholdbased on the pillar width, the decode threshold, and a second constantwhen the at least the write threshold number of the set of encoded dataslices does not have the desired revision level. For example, theprocessing module determines the retrieval threshold in accordance withthe formula retrieval threshold=n−k+1. For instance, the processingmodule establishes the retrieval threshold to be 21 when the pillarwidth is 30, the decode threshold is 10, and the second constant is 1.Such establishing of the retrieval threshold may provide a systemimprovement by eliminating the possibility that another group of encodeddata slices exists in the DS unit storage set, wherein the another groupof encoded data slices are associated with a common revision level andare unavailable (e.g., DS unit off-line, a network failure).

The method continues at step 238 where the processing module selects DSunits for retrieval from the DS unit storage set to produce selected DSunits. Such a selection may be based on one or more the DS unit storageset, the error coding dispersal storage function parameters, theretrieval threshold, DS unit performance history, a number of encodeddata slices retrieved so far, a comparison of the encoded data slicesretrieved so far to the retrieval threshold, retrieval requirements, DSunits that are known to have successfully stored a most recent revision,DS unit attributes, DS unit status, DS unit availability, estimated DSunit performance, estimated DS units reliability, estimated DS unitavailability, and DS unit cost.

The method continues at step 240 where the processing module issues dataretrieval requests to the DSN (e.g., to the selected DS units) for theset of encoded data slices. The method continues at step 242 where theprocessing module receives encoded data slices of the set of encodeddata slices to produce received encoded data slices. The methodcontinues at step 244 where the processing module determines whether anumber of received encoded data slices compares favorably to theretrieval threshold. For example, the processing module determines thatthe number of received encoded data slices compares favorably to theretrieval threshold when the number of encoded data slices is greaterthan or equal to the retrieval threshold. As another example, theprocessing module determines that the number of received encoded dataslices compares favorably to the retrieval threshold by determiningwhether at least a decode threshold number of the received encoded dataslices have a revision number corresponding to a desired revision level.In such a scenario, the processing module indicates a favorablecomparison when the at least the decode threshold number of the receivedencoded data slices have the revision number corresponding to thedesired revision level.

The method repeats back to step 238 when the processing moduledetermines that the number of received encoded data slices does notcompare favorably to the retrieval threshold. In such a scenario, theprocessing module may select different DS units of the DSN for retrievalto try again. The method continues to step 246 to decode the receivedencoded data slices to recapture the data when the number of receivedencoded data slices compares favorably to the retrieval threshold.

The method continues at step 246 where the processing module determineswhether at least a decode threshold number of the received encoded dataslices have a revision number corresponding to a desired revision level.The method branches to step 252 when the processing module determinesthat the at least the decode threshold number of received encoded dataslices does have the revision number corresponding to the desiredrevision level. The method continues to step 250 when the processingmodule determines that the at least the decode threshold number ofreceived encoded data slices do not have the revision numbercorresponding to the desired revision level.

The method continues at step 250 where the processing determines whetherthe at least the decode threshold number of the received encoded dataslices have a revision number corresponding to a second desired revisionlevel (e.g., when a second exists and prefer a second over the first)when the at least the decode threshold number of the received encodeddata slices does not have the revision number corresponding to thedesired revision level. The method branches to step 254 when theprocessing module determines that the at least the decode thresholdnumber of received encoded data slices does not have the revision numbercorresponding to the second desired revision level. The method continuesto step 252 when the processing module determines that the at least thedecode threshold number of received encoded data slices does have therevision number corresponding to the second desired revision level. Themethod continues at step 252 where the processing module indicates afavorable comparison and decodes the received encoded data slices torecapture the data.

The method continues at step 254 where the processing module determineswhether at least one encoded data slice of the set of encoded dataslices is unreceived (e.g., not included in the received encoded dataslices) and accessible (e.g., retrievable). Such determining includesdetermining a deficiency number of encoded data slices based on adifference between the decode threshold number and a number of thereceived encoded data slices that have the revision number correspondingto the desired revision level, determining whether at least thedeficiency number of encoded data slices is unreceived and is accessibleand indicating that the at least one encoded data slice of the set ofencoded data slices is unreceived and accessible when the at least thedeficiency number of encoded data slices is unreceived and isaccessible, and indicating that the at least one encoded data slice ofthe set of encoded data slices is not unreceived or is not accessiblewhen the at least the deficiency number of encoded data slices is notunreceived or is not accessible.

The method branches to step 258 when the processing module determinesthat the at least one encoded data slices is unreceived and accessible.The method continues to step 256 when the processing module determinesthat the at least one encoded data slices is not unreceived or is notaccessible. The method continues at step 256 where the processing modulesends an error message (e.g., to the requester, to a DS managing unit).Alternatively, the method repeats back to step 238 to try again (e.g.,waiting for the at least one encoded data slices to become accessible).

The method continues at step 258 where the processing module reissuesthe data retrieval requests to the DSN for the at least one encoded dataslice and receives one or more of the at least one encoded data slice toproduce additionally received encoded data slices when the at least oneencoded data slice of the set of encoded data slices is unreceived andaccessible. The method continues at step 260 where the processing moduledecodes the received encoded data slices to recapture the data when anumber of the received encoded data slices and the additionally receivedencoded data slices compares favorably to the retrieval threshold (e.g.,have a decode threshold number of encoded data slices).

Alternatively, the processing module may utilize a consistency threshold(e.g., retrieval threshold=n−k+1) when accessing encoded data slices tobe deleted. In such a scenario, there will be less than a writethreshold number of encoded data slices remaining in the DS unit storageset. Alternatively, the processing module may utilize the consistencythreshold when accessing encoded data slices to produce a rebuiltencoded data slice subsequent to re-creating a corresponding datasegment. In such a scenario, the rebuilt encoded data slice isre-created from the DS unit storage set such that less than a writethreshold number of encoded data slices are remaining in the DS unitstorage set (e.g., implying that a latest visible revision may beutilized to produce the rebuilt encoded data slice). The method toproduce a rebuilt encoded data slice associated an encoding ratio ofn−k>k is discussed in greater detail with reference to FIG. 12.

FIG. 12 is a flowchart illustrating an example of synchronizing arevision of stored data. Such synchronizing may include rebuilding anencoded data slice and/or deleting an un-required encoded data slicewhen the encoded data slice or the un-required encoded data slice areincluded in a set of encoded data slices where a pillar width n is atleast twice a read threshold k. In such a scenario, the a processingmodule may decode a data segment to enable rebuilding of the encodeddata slice from at least two groups of encoded data slices of a set ofencoded data slices. For example, the processing module may dispersedstorage error decode encoded data slices retrieved from dispersedstorage (DS) units 1-5 or from DS units 6-10 to produce the data segmentwhen the pillar width n=10 and the read threshold k=5. Such a datasegment may be stored as two or more revisions when the pillar width nis at least twice the read threshold k and when an error occurred in astorage sequence (e.g., a decode threshold number of offline DS unitsmiss the storage of a newer revision of the data segment).

The method begins with step 261 where a processing module determinesrevisions with at least a decode threshold number of encoded dataslices. Such determining of the revisions includes retrieving encodeddata slices and corresponding revision information from as many pillarsas possible for a data segment that is stored in a DS unit storage set.Such determining of the revisions may occur when a DS unit isreactivated after being off-line and/or when a time period has elapsedsince a previous determination of revisions.

The method continues at step 262 where the processing module identifiesa revision with less than a decode threshold number of encoded dataslices. The processing module may not be able to reconstruct the datasegment corresponding to the revision when all of the encoded dataslices were retrieved (e.g., a decode threshold number is notavailable). The processing module may be able to reconstruct the datasegment corresponding to the revision when a number of unretrievedencoded data slices is greater than or equal to a number of encoded dataslices required to decode the data segment (e.g., a difference betweenthe decode threshold and a number of encoded data slices received so farof the same revision).

The method continues at step 263 where the processing module determineswhether the revision with less than a decode threshold number of encodeddata slices is older than a revision with a decode threshold number ofencoded data slices. A storage capacity efficiency enhancement may berealized when slices of older revisions are deleted when slices of newerrevisions exist that can be utilized to reconstruct a data segment. Themethod branches to step 266 when the processing module determines thatthe revision with less than a decode threshold number of encoded dataslices is older than the revision with a decode threshold number ofencoded data slices. The method continues to step 264 when theprocessing module determines that the revision with less than a decodethreshold number of encoded data slices is not older than the revisionwith a decode threshold number of encoded data slices. In such ascenario, it may be possible to reconstruct a data segment associatedwith a newer revision if the decode threshold number of encoded dataslices can be retrieved for the newer version (e.g., a decode thresholdnumber of total as compared to what may have been received so far).

The method continues at step 264 where the processing module determineswhether it is possible for the revision with less than a thresholdnumber of pillars to have a threshold number of pillars. Such adetermination may be based on comparing a difference between the pillarwidth and a number of encoded data slices received so far to adifference between the decode threshold and a number of encoded dataslices received for the revision with less than a decode thresholdnumber of pillars. The method repeats back to step 262 when theprocessing module determines that it is possible for the revision withless than a decode threshold number of pillars to have the decodethreshold number of encoded data slices. The method continues to step266 when the processing module determines that it is not possible forthe revision with less than a decode threshold number of encoded dataslices to have a decode threshold number of encoded data slices.

The method continues at step 266 where the processing module deletesencoded data slices associated with the revision with less than thedecode threshold number of encoded data slices since it is not possiblefor the revision to have the decode threshold number of encoded dataslices and/or the revision is older than a revision that it is availablenow. Such deletion includes sending a delete command with correspondingslice names to DS units to delete the slices of the revision with lessthan the decode threshold number of encoded data slices.

The method continues at step 268 where the processing module facilitatesrebuilding a latest revision with a decode threshold number of encodeddata slices. Such facilitating includes sending a rebuild message to astorage integrity processing unit that includes slice names associatedwith the latest revision requiring rebuilding and rebuilding all encodeddata slices associated with the data segment to the latest revision byretrieving a decode threshold number of encoded data slices associatedwith the latest revision, dispersed storage error decoding the thresholdnumber of encoded data slices to produce a set of encoded data slices,and sending the set of encoded data slices to the DS unit storage setfor storage therein.

FIG. 13 A is a diagram illustrating another example of a memoryutilization map where a memory utilization of a memory device 1 iscompared to a memory utilization of a memory device 2 for both anunbalanced state and a balanced state after a memory balancing functionhas been executed as described in greater detail with reference to FIG.13 B. In an implementation example, memory device 1 and memory device 2are be implemented in a common dispersed storage (DS) unit. In anotherimplementation example, memory device 1 and memory device 2 areimplemented in two different DS units. The shaded area of the memorydevice utilization figure indicates a proportion of utilization relativeto the capacity of the memory device. A memory mapping of unbalancedmemory devices 270 indicates that memory device 2 is utilizing more ofthe capacity of memory device 2 as compared to the utilization of memorydevice 1 when the memory utilization is unbalanced.

The memory devices 1 and 2 may each be assigned to a slice address rangecorresponding to encoded data slices to be stored in the memory device(e.g., a slice name range). For example, memory device 1 is assigned toan address range of 125-136 and memory device 2 is assigned to anaddress range of 137-185 when the memory devices are unbalanced. In anexample of operation, memory device 1 and memory device 2 areimplemented in DS unit 5 wherein the DS unit 5 is utilized to storeencoded data slices. DS unit 5 has stored more bytes of encoded dataslices in memory device 2 as compared to bytes of encoded data slicesstored in memory device 1 when the memory devices are unbalanced. Insuch a scenario, DS unit 5 may determine to execute a memory balancingfunction to balance the utilization of memory device 1 and memory device2.

The memory utilization of memory device 1 and memory device 2 isbalanced (e.g., approximately the same utilization) following theexecution of the memory balancing function. Such a memory balancingfunction may result in the transfer of encoded data slices from memorydevice 2 to memory device 1 and the address range may be modified suchthat memory device 1 is assigned to an address range of 125-142 andmemory device 2 is assigned to an address range of 143-185 when thememory devices are balanced as in the memory mapping of bounced memorydevices 272. In such a scenario, some of the slice addresses werereassigned from an over utilized memory device to an underutilizedmemory device. The method of the memory balancing function is discussedin greater detail with reference to FIG. 13 B.

FIG. 13 B is a flowchart illustrating another example of balancingmemory utilization. The method begins with step 274 where a processingmodule determines memory devices to consider balancing. Such memorydevices may include one or more of a single memory device, an array ofmemory devices, a dispersed storage (DS) unit that includes a pluralityof memory devices, a plurality of DS units within a dispersed storagenetwork (DSN) memory, and a plurality of DSN memories. Such adetermination may be based on one or more of where a balancing processleft off last time, a query, an error message, a command, apredetermination, and a list.

The method continues at step 276 where the processing module determinesutilization of the memory devices. Such utilization may indicate one ormore of an amount of storage used, an amount of storage utilized as apercentage of a capacity of the memory device, an amount of storageutilized by a category (e.g., based on a priority indicator, a securityindicator, a performance indicator, a user identifier (ID), a vault ID,an affiliated group, etc.), and an amount of unused available capacity.Such a utilization determination may be based on one or more of a query,and memory analysis, a list, a ping, a message, a command, an errormessage, and lookup.

The method continues at step 280 where the processing module determineswhether to balance the utilization of the memory devices. Such adetermination may be based on one or more of the memory devices, theutilization of the memory device, a difference in utilization of memorydevices, a utilization difference threshold, a comparison of thedifference in utilization of memory devices to the utilizationdifference threshold, an estimated impact to balance utilization of thememory devices, and one or more different groupings of two or morememory devices. For example, the processing module determines to balancewhen a difference in utilization of the memory devices is greater than autilization difference threshold. The method branches to step 282 whenthe processing module determines to balance the utilization of thememory devices. The method repeats back to step 274 when the processingmodule determines not to balance the utilization of the memory devices.Note that the processing module may recursively determine differentgroupings of memory devices to determine a combination to balance (e.g.,memories 1/2, memories 2/3, memories 1/3, etc.).

The method continues at step 282 where the processing module determineshow to balance utilization of the memory devices. For example, theprocessing module may determine to move the slice name address boundarythat splits an address range between the two or more memory devicesand/or transfer encoded data slices from a memory device with a higherutilization to a memory device with a lower utilization followed byupdating a virtual DSN address to physical location table. Such adetermination may be based on one or more of the utilization of thememory devices, a capacity of the memory devices, an address range ofassignments, size of the stored data slices, an estimation of a numberof encoded data slices to transfer based on a size of the encoded slicesto equalize memory device utilization, a predetermination, a lookup, amessage, and a command.

The method continues at step 284 where the processing module transfersencoded data slices from a first memory device to a second memory devicewherein the first memory device is more utilized in the second memorydevice. In addition, the processing module may delete or overwrite theencoded slices transferred from the first memory device when theprocessing module has confirmed that the encoded data slices weresuccessfully transferred to the second memory device.

The method continues at step 286 where the processing module re-assignsslice address range assignments of the first memory device and thesecond memory device. Such reassigning includes assigning a portion ofslice name address ranges previously utilized by the first memory deviceto be assigned to slice name address ranges of the second memory device.The processing module may repeat the method producing a cascade effectafter moving a first block of slices from the first memory device to thesecond memory device. For example, the second memory element may appearover utilized by comparison to a third memory element after transferringencoded data slices from memory device 1 to memory device 2.

FIG. 14 A is a flowchart illustrating an example of identifying a failedmemory device. The method begins with step 288 where a processing moduledetects a failed memory device. Such a determination may be based on oneor more of a query, an error message, a failed transaction indicator, amemory device removal indicator, a message, and a command. The methodcontinues at step 290 where the processing module determines a dispersedstorage network (DSN) address range associated with the failed memorydevice. Such a determination may be based on one or more of a virtualDSN address to physical location table lookup, a query, a message, and acommand. The method continues at step 292 where the processing modulesends the DSN address range of the failed memory device to one or moreof a dispersed storage (DS) processing unit, a DS managing unit, astorage integrity processing unit, a user device, and a DS unit. Suchsending of the DSN address range may invoke a memory device accessrestriction method as described in greater detail with reference to FIG.14 B.

FIG. 14 B is a flowchart illustrating an example of processing a memoryaccess request. The method begins with step 294 where a processingmodule receives a dispersed storage network (DSN) memory access request.Such a request may include one or more of a user identifier (ID), a dataobject name, a priority indicator, a security indicator, a performanceindicator, access requirements, metadata, and an access command. Notethat the access command may include one of but not limited to a storecommand, a retrieve command, a delete command, and a list command.

The method continues at step 296 where the processing module determinesrequired DSN address ranges for a plurality of sets of encoded dataslices corresponding to the DSN memory access request. Such adetermination may be based on one or more of a data object name, a userID, a vault ID, a vault lookup, a virtual DSN address to physicallocation table lookup, a source name determination, a slice namedetermination, a predetermination, a message, and a command. Forexample, the processing module determines a source name based on thedata object name and a vault ID and determines a plurality of slicenames corresponding to the source name. Next, the processing moduledetermines the required DSN address ranges based on a virtual DSNaddress to physical location table lookup utilizing the plurality ofslice names as an index.

The method continues at step 298 where the processing module determinesfailed memory devices corresponding to the required DSN address ranges.Such a determination may be based on one or more of a failed addressrange list, a received DSN address range of a failed memory device, therequired DSN address range, a query, a message, and a command. Forexample, the processing module receives one or more messages indicatinga DSN address range of one or more failed memory devices. The processingmodule aggregates the messages into a failed address range list andutilizes the list to determine the failed memory devices of the requiredDSN address ranges by comparing the addresses of a list to the requiredDSN address ranges.

The method continues at step 300 where the processing module determineswhether too many memory devices have failed of the required DSN addressranges by comparing a number of failed memory devices of the requiredDSN address ranges to a failure threshold. For example, the processingmodule determines that too many memory devices have failed of therequired DSN address ranges when the number of failed memory devices ofthe required DSN address ranges is greater than the failure threshold.The method branches to step 304 when the processing module determinesthat too many memory devices have not failed. The method continues tostep 302 when the processing module determines that too many memorydevices have failed. The method continues at step 302 where theprocessing module rejects the request. Such rejecting includes sending areject message to a requester and/or to a dispersed storage (DS)managing unit.

The method continues at step 304 where the processing module processesthe DSN memory access request when the processing module determines thattoo many memory devices have not failed. Such a method may providecomputing system network utilization efficiency improvement since dataslice retrievals will not be attempted when there are too many memorydevice failures.

FIG. 15 is another schematic block diagram of an embodiment of acomputing system that includes a user device 12, at least one dispersedstorage (DS) processing unit 16 of a plurality of DS processing units1-N, and at least one dispersed storage network (DSN) memory 22 of aplurality of DSN memories 1-N. For example, as illustrated, thecomputing system may include N DS processing units 1-N and N DSNmemories 1-N. As another example, the computing system may include oneDS processing unit and N DSN memories. As yet another example, thecomputing system may include N DS processing units 1-N and one DSNmemory. Each DS processing unit 1-N may be implemented utilizing anauthentication server.

Such a user device 12 includes a credential package 306, a share encoder308, a plurality of random number generators (RNG) 1-N, a plurality ofkey generators 1-N, and a plurality of encryptors 1-N. Such a credentialpackage 306 may include a credential 310 and a credential hash digest312. Such a credential 310 may include sensitive data including one ormore of a private key, a public key, a signed certificate, confidentialuser information, a password, and any sensitive confidentialinformation. Such a credential hash digest 312 may be generated byutilizing a hash function on the credential 310. Such a credential hashdigest 312 may be utilized in a subsequent integrity verification stepto verify that the credential 310 has not been tampered with.

Such a share encoder 308 encodes the credential package 306 to produceencoded shares 1-N in accordance with a share encoding function (e.g.,Shamir secret sharing algorithm). Such encryptors 1-N encrypt theencoded shares 1-N in accordance with an encryption algorithm utilizingkeys 1-N to produce encrypted shares 1-N. Generation of the keys 1-N isdiscussed in greater detail below. Such an encryption algorithm may bein accordance with dispersed storage error coding parameters associatedwith the user device 12. For example, each of the encryptors 1-N utilizea common encryption algorithm in accordance with the dispersed storageerror coding parameters. As another example, at least two encryptors ofthe encryptors 1-N utilize different encryption algorithms in accordancewith the dispersed storage error coding parameters.

The encryptors 1-N output the encrypted shares 1-N to the DS processingunits 1-N. The DS processing units 1-N dispersed storage error encodeseach encrypted share of the encrypted shares 1-N to produce N groups ofencoded share slices in accordance with the error coding dispersalstorage function parameters, wherein each group of encoded share slicesincludes one or more sets of encoded data slices. The DS processingunits 1-N send the N groups of encoded share slices to the DSN memories1-N for storage therein. Alternatively, the functionality of the DSprocessing unit (e.g., DS processing 34) may be included in the userdevice 12 such that the user device 12 dispersed storage error encodesthe encrypted shares 1-N to produce the N groups of encoded shareslices. Next, the user device 12 sends the N groups of encoded shareslices to the DSN memories 1-N for storage therein. Alternatively, theencryptors 1-N output the encrypted shares 1-N to one or more of the DSNmemories 1-N for storage therein (e.g., without producing N groups ofencoded share slices). Alternatively, the DS processing units 1-N sendthe encrypted shares 1-N to the one or more of the DSN memories 1-N forstorage therein.

Such random number generators 1-N generate a plurality of random numberse₁-e_(N). For example, random numbers e₁-e_(N) are each a same number ofbits as a number of bits of p, where p is determined by securityparameters (e.g., of the dispersed storage error coding parameters). Therandom number generators 1-N output the plurality of random numberse₁-e_(N) to the DS processing units 1-N. The DS processing units 1-Ndispersed storage error encodes each random number of the plurality ofrandom numbers in accordance with the dispersed storage error codingparameters to produce N groups of encoded random number slices, whereineach group of encoded random number slices includes at least one set ofrandom number slices. Next, the DS processing units 1 send the groups ofencoded random number slices to the DSN memories 1-N for storagetherein. Alternatively, the user device 12 dispersed storage errorencodes the plurality of random numbers to produce the N groups ofencoded random number slices. Next, the user device 12 sends the Ngroups of encoded random number slices to the DSN memories 1-N forstorage therein. Alternatively, the user device 12 sends the pluralityof random numbers e₁-e_(N) to the one or more of the DSN memories 1-Nfor storage therein.

Such key generators 1-N generate the keys 1-N based on one or more ofthe plurality of random numbers e₁-e_(N), the security parameters, and acommon password 314. Such a common password may be utilized from time totime by a user of the user device 12 to gain access to services,information, and/or functions provided by the user device. Such a commonpassword may be obtained by one or more of receiving a user input, aretrieval, received from a flash memory device, and receiving themessage. For example, the user device 12 receives a user input of tenalphanumeric characters via a user interface input.

Such generation of the keys 1-N based on the security parametersproduces each key of the keys 1-N such that each key includes a samenumber of bits as a number of bits of p. For example, the key generators1-N generate the keys 1-N by transforming an expansion of the commonpassword utilizing a mask generating function (MGF) and the plurality ofrandom numbers in accordance with an expression key x=((MGF(commonpassword))²)^(e) _(x) modulo p. For instance, key generator 1 generateskey 1=((MGF(password))²)^(e) ₁ modulo p. Such a MGF produces adeterministic pattern of bits of any desired length based on an input.For instance, the generator 1 calculates key 1=13 when MGF (commonpassword)=4, e₁=10, and p=23, as (4²)¹⁰ mod 23=13. Alternatively, or inaddition to, the key may be further processed to provide a key of adesired length in relation to an encryption algorithm. For example, thekey output of the algorithm is hashed to produce a hashed key and adesired number of bits (e.g., 256, 192, 128 bits) of the hashed key areutilized as a key for the encryption algorithm.

The common password 314 and a decode threshold number of pairs of storedrandom numbers and encrypted shares are required to reproduce thecredential package. Note that a security improvement is provided by thesystem when the pairs of stored random numbers and encrypted shares arestored on substantially different authentication servers and/or via twoor more DS processing units and two or more DSN memories since alikelihood of a successful attack to gain access to the pairs of storedrandom numbers and encrypted shares is reduced. The reproduction of thecredential package is discussed in greater detail with reference toFIGS. 17-19. The method of operation to store the credential package isdiscussed in greater detail with reference to FIG. 16.

FIG. 16 is a flowchart illustrating an example of storing data. Themethod begins with step 316 where a processing module determinessecurity parameters to be utilized in the storing of sensitive data(e.g., a credential package). Such security parameters may include oneor more of a share number N, a value of security algorithm constant p(e.g., a prime number), a value of security algorithm constant q (e.g.,a prime number), shared secret algorithm parameters, an encryptionalgorithm indicator, a key generator function indicator, a key size, arandom number generator function, a random number size, a hash functiontype indicator, a security package structure indicator, and any otherparameter to specify the operation of the storing of the sensitive data.Such a determination of the security parameters may be based on one ormore of security requirements, a security status indicator, a useridentifier (ID), a vault ID, a list, a table lookup, a predetermination,a message, and a command. For example, the processing module determinesthe security parameters based on a table lookup corresponding to a userID affiliated with a user device.

The method continues at step 318 where the processing module generatesthe sensitive data in accordance with the security parameters. Forexample, the processing module generates the sensitive data to include acredential and a credential hash digest. For example, the processingmodule generates a hash digest of a private key and bundles the hashdigest with the private key to create a credential package as thesensitive data.

The method continues at step 320 where the processing module applies ashare encoding function on the data (e.g., the credential package) toproduce a plurality of encoded shares. Such a share encoding functionincludes at least one of a dispersed storage error encoding function anda secret sharing function. Such a secret sharing function includes atleast one of Shamir's secret sharing scheme, Blakely's scheme, and aChinese Remainder Theorem scheme. For example, the processing moduleproduces encoded shares 1-16 in accordance with shared secret algorithmparameters when N=16 and the share encoding function includes the secretsharing function. As another example, the processing module dispersedstorage error encodes the data in accordance with dispersed storageerror coding parameters to produce encoded shares 1-N when the shareencoding function includes the dispersed storage error coding function.

The method continues at step 322 where the processing module obtains acommon password. Such obtaining may be based on one or more of a userinput, a dispersed storage (DS) managing unit input, a query, a prompt,a retrieval from a memory storage device, an algorithm, a lookup, amessage, and a command. For example, the processing module obtains a 10character common password via an input user interface.

The method continues at step 324 where the processing module generates acorresponding plurality of random numbers for the plurality of encodedshares. Such generating of the corresponding plurality of random numbersincludes obtaining (e.g., generate, receive in a message, retrieve froma random number generator) a plurality of base random numbers andexpanding each base random number of the plurality of base randomnumbers based on the security parameters to produce the correspondingplurality of random numbers. For example, processing module expands thebase set of random numbers such that each random number of thecorresponding plurality of random numbers is 1,024 bits in length (e.g.,p is 1,024 bits in length).

The method continues at step 326 where the processing module generatesan encryption key for each encoded share of the plurality of encodedshares based on the common password and a corresponding one of thecorresponding plurality of random numbers. Such generating of theencryption key includes transforming the common password utilizing amask generating function, the security parameters, and the correspondingone of the corresponding plurality of random numbers. For example, theprocessing module generates a key x based on the common password and thecorresponding random number e_(x) in accordance with the expression keyx=((MGF(common password))²)^(e) _(x) modulo p.

The method continues at step 328 where the processing module encryptsthe encoded share utilizing the encryption key to produce an encryptedshare. Such encryption may be based on one or more of the securityparameters, the dispersed storage error coding parameters, a useridentifier (ID), a vault ID, a vault lookup, security requirements, asecurity status indicator, a message, and a command.

The method continues at step 330 where the processing module determinesif all N of the encoded shares 1-N have been encrypted. Such adetermination may be based on comparing a number of encrypted sharesproduced so far to the value of N. The method repeats back to step 326when the processing module determines that all N encrypted shares havenot been produced. The method continues to step 332 when the processingmodule determines that all N encrypted shares have been produced.

The method continues at step 332 where the processing module facilitatesstorage of the corresponding plurality of random numbers and each of theencrypted shares. Such facilitating includes at least one of sending theencrypted share and the corresponding one of the corresponding pluralityof random numbers to a dispersed storage (DS) processing unit, dispersedstorage error encoding the encrypted share to produce a plurality ofencoded share slices and outputting the plurality of encoded shareslices for storage (e.g., send to a dispersed storage network memory),and dispersed storage error encoding the corresponding one of thecorresponding plurality of random numbers to produce a plurality ofencoded random number slices and outputting the plurality of encodedrandom number slices for storage (e.g., send to a dispersed storagenetwork memory).

FIG. 17 is another schematic block diagram of an embodiment of acomputing system that includes a user device 12, at least one dispersedstorage (DS) processing unit 16 of a plurality of DS processing units1-N, and at least one dispersed storage network (DSN) memory 22 of aplurality of DSN memories 1-N. For example, as illustrated, thecomputing system may include N DS processing units 1-N and N DSNmemories 1-N. As another example, the computing system may include oneDS processing unit and N DSN memories. As yet another example, thecomputing system may include N DS processing units 1-N and one DSNmemory. Each DS processing unit 1-N may be implemented utilizing one ormore of a DS processing unit 16 of FIG. 1, a web server, a DS unit, andan authentication server.

Such a user device 12 includes a credential package 306, a share decoder336, a plurality of random number generators (RNG) 1-N, a plurality ofblinded password generators 1-N, a plurality of value generators 1-N, aplurality of key regenerators 1-N, and a plurality of decryptors 1-N.Such a credential package 306 may include a credential 310 and acredential hash digest 312. Such a DS processing unit of the DSprocessing units 1-N includes a DS processing module and a passkeygenerator. For example, DS processing units 1-N each include a DSprocessing module of DS processing modules 1-N and a passkey generatorof passkey generators 1-N. Alternatively, the user device 12 includesthe functionality of the DS processing units 1-N.

Such random number generators 1-N generate blinded random numbersb₁-b_(N). For example, each random number generator of the random numbergenerators 1-N generates a blinded random number of the blinded randomnumbers b₁-b_(N) such that each blinded random number includes a samenumber of bits as a number of bits of p, wherein p is extracted fromdispersed storage error coding parameters and/or security parameters.The random number generators 1-N send the blinded random numbersb₁-b_(N) to the blinded password generators 1-N and to the valuegenerators 1-N.

Such blinded password generators 1-N generate blinded passwords 1-N(e.g., bpass 1-N) based on the blinded random numbers b₁-b_(N), a commonpassword 314, and security parameters. Such generation includestransforming an expansion of the common password utilizing a maskgenerating function (MGF) and a corresponding one of the blinded randomnumbers b₁-b_(N) in accordance with the expression bpass x=((MGF(commonpassword))²)^(b) _(x) modulo p. For example, bpass 1=((MGF(commonpassword))²)^(b) ₁ modulo p. In an instance, the blinded passwordgenerator 1 calculates bpass 1=18 when MGF(common password)=4, b₁=7, andp=23, since (4²)⁷ mod 23=18. The blinded password generators 1-N sendthe blinded passwords 1-N to the passkey generators 1-N.

Such value generators 1-N generate values v₁-v_(N) based on the blindedpasswords b₁-b_(N) and the value of a security parameter constant q ofthe security parameters in accordance with the expression b*v moduloq=1. Such a security parameter constant q may be based on the value of pin accordance with the expression q=(p−1)/2. For instance, q=11 whenp=23. In an example of generating a value, value generator 1 generates avalue v1=8 when b₁=7 and q=11 (e.g., 7*8=56; 56 modulo 11=1). The valuegenerators 1-N send the values v₁-v_(N) to the key regenerators 1-N.

Such passkey generators 1-N may retrieve stored random number values ofe₁-e_(N) from the DS processing modules 1-N in response to receiving aretrieve credential package request from the user device 12. Forexample, a DS processing module of the DS processing modules 1-Nretrieves at least a dispersal decode threshold number of encoded storedrandom number slices from one or more DSN memories 1-N, dispersedstorage error decodes the at least the dispersal decode threshold numberof encoded stored random number slices to produce a stored random numberof the stored random numbers e₁-e_(N), and sends the stored randomnumber to a corresponding passkey generator of the passkey generators1-N.

Such passkey generators 1-N generate passkeys 1-N based on the storedrandom numbers e₁-e_(N) and the blinded passwords 1-N in accordance withthe expression passkey x=(bpass x)^(e) _(x) modulo p. For instance,passkey generator 1 generates a passkey 1=9 when bpass 1=18, e₁=10, andp=23 (e.g., since (18)¹⁰ modulo 23=9). The passkey generators 1-N sendthe passkeys 1-N to the key regenerators 1-N. Such key regenerators 1-Nregenerate keys 1-N based on the passkeys 1-N and the values v₁-v_(N) inaccordance with the expression key x=(passkey x)^(v) _(x) modulo p. Forinstance, key regenerator 1 regenerates key 1 such that key 1=13 whenpasskey 1=9, v1=8, and p=23 (e.g., since (9)⁸ modulo 23=13). The keyregenerators 1-N send keys 1-N to the decryptors 1-N.

Such a DS processing module of the DS processing modules 1-N retrieves(e.g., from one or more of the DSN memories 1-N) and dispersed storageerror decodes at least a dispersal decode threshold number of encodedencrypted share slices to produce an encrypted share of encrypted shares1-N in response to a retrieval request received from the user device 12.The DS processing modules 1-N send the encrypted shares 1-N to thedecryptors 1-N. The decryptors 1-N decrypt the encrypted shares 1-Nutilizing keys 1-N in accordance with a decryption algorithm to produceshares 1-N. Such a decryption algorithm may be in accordance with thedispersed storage error coding parameters and/or the securityparameters. For example, each of the decryptors 1-N utilize a commondecryption algorithm in accordance with security parameters. As anotherexample, at least two of the decryptors 1-N utilize a differentdecryption algorithm in accordance with the security parameters. Thedecryptors 1-N send the shares 1-N to the share decoder 336.

Such a secret share decoder 336 decodes the shares 1-N to reproduce thecredential package 306. Such decoding may include at least one ofdispersed storage error decoding the shares 1-N to reproduce the dataand decoding the set of shares utilizing a secret sharing function toreproduce the data. For example, the share decoder 336 decodes the setof shares utilizing a Shamir secret sharing algorithm. The method toretrieve such a securely stored credential package is discussed ingreater detail with reference to FIGS. 18-19.

FIG. 18 is a flowchart illustrating another example of retrieving datathat include similar steps of FIG. 16. The method begins with steps 316and 322 of FIG. 16 where a processing module determines securityparameters and obtains a common password. The method continues at step342 where the processing module generates a set of blinded randomnumbers. Such generating includes obtaining a set of base random numbers(e.g., generate, receive in a message, retrieve from a random numbergenerator) and expanding each base random number of the set of baserandom numbers based on security parameters to produce the set ofblinded random numbers. For example, the processing module generates aset of base random numbers and expands each base random number of theset of base random numbers in accordance with a security constant p ofthe security parameters to produce a set of blinded random numbers suchthat each blinded random number includes a same number of bits as anumber of bits of p.

The method continues at step 344 where the processing module generates aset of blinded passwords based on a common password and the set ofblinded random numbers.

Such generating of the set of blinded passwords includes, for eachblinded random number of the set of blinded random numbers, transformingthe common password utilizing a mask generating function and the blindedrandom number to produce a blinded password of the set of blindedpasswords. For example, the processing module generates a blindedpassword x of the set of blinded passwords based on the common passwordand a corresponding blinded random number b_(x) in accordance with theexpression blinded password x=((MGF(common password))²)^(b) _(x) modulop.

The method continues at step 346 where the processing module transformsthe blinded random number utilizing a modulo function based on thesecurity parameters to produce a value of a set of values for eachblinded random number of the set of blinded random numbers. For example,the processing module generates a value v_(x) of the set of values basedon a blinded random number b_(x) in accordance with the expression b*vmodulo q=1, wherein q is a security constant of the security perimeterssuch that q=(p−1)/2. For instance, v=b̂(q−2) mod q, when q is prime(e.g., 8=7̂9 mod 11, 8*7 mod 11=1).

The method continues at step 348 where the processing module sends apasskey x request that includes the blinded password x to a dispersedstorage (DS) processing module x (e.g., of a DS processing unit, a DSunit, a web server, an authentication server). The method continues atstep 350 where the processing module receives a passkey x from the DSprocessing module x in response to the passkey x request. The method ofoperation of the DS processing module x is discussed in greater detailwith reference to FIG. 19. Alternatively, the processing modulefunctions in accordance with the method of the DS processing module x toproduce the passkey x.

The method continues at step 352 where the processing module determineswhether the set of passkeys has been produced, wherein the set ofpasskeys includes at least a share function decode threshold number ofpasskeys. The method repeats back to step 346 will processing moduledetermines that the set of passkeys has not been produced. The methodcontinues to step 354 when the processing module determines that the setof passkeys has been produced.

The method continues at step 354 where the processing module generates aset of decryption keys based on the set of values (e.g., generated basedon the set of blinded random numbers) and the set of passkeys. Suchgenerating includes transforming each passkey of the set of passkeysutilizing a modulo function based on security parameters and acorresponding value of the set of values to produce a decryption key ofthe set of decryption keys. For example, the processing module generateskey x based on the value v_(x) and passkey x in accordance with theexpression key x=(passkey x)^(v) _(x) modulo p.

The method continues at step 356 where the processing module retrievesat least a decode threshold number of encrypted shares to produce a setof encrypted shares, wherein the set of encrypted shares corresponds tothe set of stored random numbers. Such retrieving includes at least oneof outputting at least one encrypted share retrieval request message toat least one DS processing to retrieve the at least the decode thresholdnumber of encrypted shares from a dispersed storage network (DSN) memoryand for each encrypted share of the set of encrypted shares, retrievinga set of encoded encrypted share slices from the DSN memory anddispersed storage error decoding the set of encoded encrypted shareslices to produce the encrypted share.

The method continues at step 358 where the processing module decryptseach encrypted share of the set of encrypted shares utilizing acorresponding decryption key of the set of decryption keys to produce aset of shares. Such decrypting may be in accordance with a decryptionalgorithm based on one or more of the security parameters, error codingdispersal storage function parameters, a user identifier (ID), a vaultID, a vault lookup, security requirements, a security status indicator,a message, and a command.

The method continues at step 360 where the processing module decodes theset of shares to reproduce data. Such decoding includes at least one ofdispersed storage error decoding the set of shares to produce the dataand decoding the set of shares utilizing a secret sharing function toproduce the data (e.g., a credential package).

The method continues at step 362 where the processing module validatesthe data when the data is a credential package. Such validating includescomparing a calculated hash of a credential of the credential package toa credential hash digest of the credential package. For example, theprocessing module determines that the credential package is valid whenthe comparison indicates that the calculated hash of the credential issubstantially the same as the credential hash digest.

FIG. 19 is a flowchart illustrating an example of generating a passkey.The method begins with step 364 where the processing module receives apasskey x request, wherein the request includes a blinded password x ofa set of blinded passwords. Alternatively, the processing modulereceives the set of blinded passwords. Such a passkey x request mayinclude a passkey x identifier, the blinded password x, a useridentifier (ID), a vault ID, a source name, one or more slice names, anda random number identifier (e.g., a data object name, a block number, asource name, a directory identifier, etc.). For example, the processingmodule receives the passkey x request from a user device, wherein therequest includes the blinded password x and a data object nameaffiliated with a desired random number e_(x).

The method continues at step 366 where the processing module retrievesat least a decode threshold number of stored random numbers to produce aset of stored random numbers. Such retrieving includes at least one ofoutputting at least one stored random number retrieval request messageto at least one dispersed storage (DS) processing unit to retrieve theat least the decode threshold number of stored random numbers from adispersed storage network (DSN) memory, for each stored random number ofthe set of stored random numbers retrieving a set of encoded storedrandom number slices from the DSN memory, and dispersed storage errordecoding the set of encoded stored random number slices to produce thestored random number. For example, the processing module retrieves a setof encoded stored random number slices corresponding to a received dataobject name affiliated with the desired random number e_(x) anddispersed storage error decodes the set of encoded stored random numberslices to produce stored random number e_(x).

The method continues at step 368 where the processing module generates aset of passkeys based on the set of blinded passwords and the set ofstored random numbers. Such generation includes transforming the blindedpassword utilizing a modulo function based on a corresponding storedrandom number of the set of stored random numbers and securityparameters to produce a passkey of the set of passkeys for each blindedpassword of the set of blinded passwords and outputting the set ofblinded passwords to a DS processing unit and receiving the set ofpasskeys. For example, the processing module generates a passkey x basedon stored random number e_(x) and blinded password x in accordance withan expression passkey x=(blinded password x)^(e) _(x) modulo p. Themethod continues at step 370 where the processing module outputs thepasskey x (e.g., to a requester).

The methods described above operate in accordance with the mathematicalexpressions described in the methods above to enable generation of keysutilized to encrypt and decrypt shares of a credential package. Themathematical expressions may be further understood in consideration ofthe following mathematical proof, wherein the proof illustrates that areproduced key (e.g., to decrypt an encrypted share) is substantiallyequivalent to an original key (e.g., utilized to encrypt the share).

Proof—Recall that:

b*v=1 mod q and p=2*q+1

Will show that:

(MGF(password)̂2)̂(b*e*v) equals (MGF(password)̂2)̂e(modulo p)

Replace MGF(password) with X:

(X̂2)̂(b*e*v)=(X̂2)̂(e)(modulo p)

Note:

Since b*v=1 mod q, it follows that: b*v=n*q+1, for some integer n. Notethat (b*v)/q=n remainder 1.Therefore (b*v) can be substituted with (n*q+1) in the above expressionyielding:

(X̂2)̂((n*q+1)*e) mod p

Since p=2*q+1, take p out of the formula, giving:

(X̂2)̂((n*q+1)*e) mod (2*q+1)

Since X̂2 is raised to a power, simply take X to the power of twice theexponent:

X̂(2*(nq+1)*e) mod (2q+1)

Which may be written as:

X̂((2nq+2)*e) mod (2q+1)

Multiplying both parts by e:

X̂(2nqe+2e) mod (2q+1)

Split these out as so:

X̂(2neq)*X̂(2e) mod (2q+1)

Re-write the first power of X:

X̂(2q*ne)*X̂(2e) mod (2q+1)

Which can also be written as:

(X̂(2q))̂(ne)*X̂(2e) mod (2q+1)

Un-doing the substitution of p for 2q+1, find:

(X̂(p−1))̂(ne)*X̂(2e) mod p

Fermat's Little Theorem shows that for any prime number P, and anyinteger X, that:

X̂(P−1)=1 mod P, therefore (X̂(p−1)) mod p=1 mod p. This yields:

1̂(ne)*X̂(2e) mod p

Which is the same as:

1*X̂(2e) mod p

Which is:

(X̂2)̂e mod p

Which is the key.

As a numerical example:

p=23

q=(p−1)/2=11

let e1=10

let [mask generating function (common password)]̂2=16

key 1=16̂e1 mod 23=13

let b1=7

bpass 1=16̂7 mod 23=18

passkey 1=bpasŝe1 mod p=18̂10 mod 23=9

b*v=1 modulo q

b1*v1=1 mod q

7*v1=1 mod 11 note: 56 mod 11=1 so v1=8

regen key 1=passkey1̂v1 modulo p

9̂8 mod 23=13, which checks with the 13 calculated above for key 1.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

The present invention has also been described above with the aid ofmethod steps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention.

The present invention has been described, at least in part, in terms ofone or more embodiments. An embodiment of the present invention is usedherein to illustrate the present invention, an aspect thereof, a featurethereof, a concept thereof, and/or an example thereof. A physicalembodiment of an apparatus, an article of manufacture, a machine, and/orof a process that embodies the present invention may include one or moreof the aspects, features, concepts, examples, etc. described withreference to one or more of the embodiments discussed herein.

The present invention has been described above with the aid offunctional building blocks illustrating the performance of certainsignificant functions. The boundaries of these functional buildingblocks have been arbitrarily defined for convenience of description.Alternate boundaries could be defined as long as the certain significantfunctions are appropriately performed. Similarly, flow diagram blocksmay also have been arbitrarily defined herein to illustrate certainsignificant functionality. To the extent used, the flow diagram blockboundaries and sequence could have been defined otherwise and stillperform the certain significant functionality. Such alternatedefinitions of both functional building blocks and flow diagram blocksand sequences are thus within the scope and spirit of the claimedinvention. One of average skill in the art will also recognize that thefunctional building blocks, and other illustrative blocks, modules andcomponents herein, can be implemented as illustrated or by discretecomponents, application specific integrated circuits, processorsexecuting appropriate software and the like or any combination thereof.

What is claimed is:
 1. A method comprises: determining a retrievalthreshold for retrieving a set of encoded data slices from a dispersedstorage network (DSN), wherein the set of encoded data slices representsdata encoded using a dispersed storage error encoding function having anumber of encoded data slices in the set of encoded data slices is equalto or greater than a decode threshold and wherein the retrievalthreshold is equal to or greater than the decode threshold; issuing dataretrieval requests to the DSN for the set of encoded data slices;receiving encoded data slices of the set of encoded data slices toproduce received encoded data slices; and when a number of receivedencoded data slices compares favorably to the retrieval threshold,decoding the received encoded data slices to recapture the data.
 2. Themethod of claim 1, wherein the set of encoded data slices comprises: afirst group of encoded data slices having a revision level, wherein anumber of encoded data slices in the first group of encoded data slicesis equal to or greater than the decode threshold; and a second group ofencoded data slices having the revision level, wherein a number ofencoded data slices in the second group of encoded data slices is equalto or greater than the decode threshold.
 3. The method of claim 1,wherein the set of encoded data slices comprises: a first group ofencoded data slices having a first revision level, wherein a number ofencoded data slices in the first group of encoded data slices is equalto or greater than the decode threshold; and a second group of encodeddata slices having a second revision level, wherein a number of encodeddata slices in the second group of encoded data slices is equal to orgreater than the decode threshold.
 4. The method of claim 1, wherein thedetermining the retrieval threshold comprises: determining whether atleast a write threshold number of the set of encoded data slices have adesired revision level; when the at least the write threshold number ofthe set of encoded data slices have the desired revision level,establishing the retrieval threshold based on the pillar width, thewrite threshold, and a first constant; and when the at least the writethreshold number of the set of encoded data slices does not have thedesired revision level, establishing the retrieval threshold based onthe pillar width, the decode threshold, and a second constant.
 5. Acomputing device comprises: an interface; a memory; and a processingmodule operably coupled to the memory, wherein the processing module isoperable to: determine a retrieval threshold for retrieving a set ofencoded data slices from a dispersed storage network (DSN), wherein theset of encoded data slices represents data encoded using a dispersedstorage error encoding function having a number of encoded data slicesin the set of encoded data slices is equal to or greater than a decodethreshold and wherein the retrieval threshold is equal to or greaterthan the decode threshold; issue, via the interface, data retrievalrequests to the DSN for the set of encoded data slices; receive, via theinterface, encoded data slices of the set of encoded data slices toproduce received encoded data slices; and when a number of receivedencoded data slices compares favorably to the retrieval threshold,decode the received encoded data slices to recapture the data.
 6. Thecomputing device of claim 5, wherein the set of encoded data slicescomprises: a first group of encoded data slices having a revision level,wherein a number of encoded data slices in the first group of encodeddata slices is equal to or greater than the decode threshold; and asecond group of encoded data slices having the revision level, wherein anumber of encoded data slices in the second group of encoded data slicesis equal to or greater than the decode threshold.
 7. The computingdevice of claim 5, wherein the set of encoded data slices comprises: afirst group of encoded data slices having a first revision level,wherein a number of encoded data slices in the first group of encodeddata slices is equal to or greater than the decode threshold; and asecond group of encoded data slices having a second revision level,wherein a number of encoded data slices in the second group of encodeddata slices is equal to or greater than the decode threshold.
 8. Thecomputing device of claim 5, wherein the processing module is furtheroperable to determine the retrieval threshold by: determining whether atleast a write threshold number of the set of encoded data slices have adesired revision level; when the at least the write threshold number ofthe set of encoded data slices have the desired revision level,establishing the retrieval threshold based on the pillar width, thewrite threshold, and a first constant; and when the at least the writethreshold number of the set of encoded data slices does not have thedesired revision level, establishing the retrieval threshold based onthe pillar width, the decode threshold, and a second constant.